Methods and compositions for assessing antibody specificities

ABSTRACT

The present invention provides compositions and methods that can be used to determine a peptide signature for an antibody repertoire in a sample comprising multiple antibodies. The method can be used to characterize a phenotype in a sample, such as providing a diagnosis, prognosis or theranosis of a medical condition.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/991,982, filed May 29, 2018, pending, which is a continuation of U.S.patent application Ser. No. 15/775,363, pending, which is the NationalStage of International Application No. PCT/US2016/061929, filed Nov. 14,2016, which claims the benefit of U.S. Provisional Application No.62/339,644, filed May 20, 2016, and 62/253,926, filed Nov. 11, 2015,each of which is herein incorporated in its entirety by reference.

SEQUENCE LISTING

The instant application contains a Sequence Listing which has beensubmitted via EFS-Web and is hereby incorporated by reference in itsentirety. Said ASCII copy, created on Jul. 11, 2019, is namedSUI001C2_Sequence_Listing.txt, and is 269,735 bytes in size.

FIELD OF INVENTION

In various embodiments, the invention relates to compositions andmethods for diagnosing disease by detecting antibodies in a sample.

BACKGROUND

All publications herein are incorporated by reference to the same extentas if each individual publication or patent application was specificallyand individually indicated to be incorporated by reference. Thefollowing description includes information that may be useful inunderstanding the present invention. It is not an admission that any ofthe information provided herein is prior art or relevant to thepresently claimed invention, or that any publication specifically orimplicitly referenced is prior art

Antibodies present in human specimens serve as the primary analyte anddisease biomarker for a large and broad group of infectious, bacterial,viral, allergic, parasitic, and autoimmune diseases. As such, hundredsof distinct antibody detecting tests (collectively referred to as“immunoassays”, have been developed to diagnose human disease usingtissue samples that include but are not limited to whole blood, serum,plasma, saliva, urine, and tissue aspirates. Immunoassays remainessential to the diagnosis of autoimmune diseases including, but notlimited to, Grave's disease, Sjogren's syndrome Celiac disease, Crohn'sdisease, Rheumatoid arthritis. Immunoassay are also widely used todiagnosis infectious diseases including for example viral infections(e.g. HIV, Hepatitis C, HSV-1, Zika virus, Epstein Barr virus, andothers), bacterial infections include for example (Streptococcus sp.,Helicobacter pylori, Borrellia burdorferi (Lyme), and others), fungalinfections (e.g. Valley Fever), parasitic infections (e.g., Trypanosomacruzi, Toxoplasma gondii, Taenia solium, Toxocara canis, and others).Furthermore, Immunoassays are often used to identify and monitorallergies (e.g. peanut allergy, milk, pollen, and others. Beyond theseareas, immunoassays have demonstrated utility for the diagnosis ofneurodegenerative disease, cardiovascular disease, and cancers.

Methods to detect antibodies include radio immunoassay (RIA), enzymelinked immunosorbant assays (ELISA), chemiluminescent assays, andprotein and peptide arrays. These assay formats share in common therequirement to develop a molecular chemical reagent that binds to theanalyte antibody in a sample in the majority of individuals withdisease, to provide sensitivity, but not to any of the many distinctantibodies present in individuals without disease, to provide diagnosticspecificity. Such reagents include antibodies, peptides, human proteins,nucleic acid aptamers, and other molecular binding entities [1, 2] [3,4]. Such reagents are often highly optimized (Ballew J et al., PNAS,2014) in order to achieve high sensitivity and specificity. Suchoptimization has been the subject of much research and development.Individual reagents, however, often possess insufficient affinity andspecificity for the analytes of interest.

Present method used to develop diagnostic immunoassays limit the overallsensitivity and specificity that can be obtained from the assay, andthus the utility, because they include extraneous antigen matter (i.e.,large proteins, peptides, lipids, whole cell lysates) that can result incross-reactive binding from unrelated antibodies. For example, Lymedisease (infection with Borrelia burgdorferi) tests use whole celllysates that contain a large number of distinct molecular compositionsthat are not targeted by the immune response Borrelia, but capture ordetect antibodies generated in response to other infections such asinfectious mononucleosis. Thus there is an unmet need for diagnostictechnologies that can identify and present only those antigen componentsthat are most specifically recognized by the immune response inindividuals with a given phenotype.

Because individual reagents often do not capture or react with asufficient number of samples from individuals with the disease (i.e.insufficient sensitivity), two or more reagents can be combined into adiagnostic test or used in parallel as an antigen panel. Nevertheless,combining sets of peptides into a single assay to increase thesensitivity of diagnosis is challenging since their non-specificbinding, that limits specificity, is generally additive thereby limitingthe overall diagnostic specificity of the assay. Experimentalidentification of the optimal combination of biochemical reagents isdifficult given the combinatorial complexity of combining and weightingthe antibody reactivities to each antigen in a panel [5, 6].

An important limitation associated with existing immunoassay formats isthat they cannot be readily combined or aggregated together.Consequently, performing a large number of tests is additive in terms ofcost and labor, thereby decrease the probability of making a correctdiagnosis. For example, if an individual is bit by a tick, they may beinfected with multiple tick-borne pathogens (there are more than 10known tick-transmitted infectious agents). In many cases, physicianswill only a test for Borrelia burgdoferi, even though any of 10s ofother organisms may have infected that individual. Thus, there is a needfor low cost multiplexed test that can diagnosis any or all of thetick-borne infections. Similarly, if a patient presents with a commonsymptom (e.g. fever, fatigue, headache), it can be difficult to identifywhich tests should be ordered to identify potential causes of thepresenting symptoms. Thus, there is a need for methods and compositionsthat can integrate many tests into a single standardized assay, and thussimultaneously test for many different diseases or infections. Thepresent invention provides solution to this problem.

The use of massively parallel DNA sequencing, also known asnext-generation sequencing (hereafter referred to as “NGS”), highthroughput sequencing, or deep sequencing, has been applied to enablethe diagnosis of human diseases [7]. These collective approaches may bereferred to generally as “NGS” throughout.

The prospect of analyzing entire human antibody repertoires has been agoal for at least several decades. Reported methods include humanproteome arrays, phage display/immunoprecipitation (Ph-IP), peptide andpeptoid arrays, and NGS analysis of antibody genes (Ig-Seq) [9][8]. Onechallenge associated with repertoire characterization is identifyingparticular peptide sequences to populate arrays limited to ˜10⁶ fields.Hence, prior methods have used small arrays of random peptides,typically having fewer than 300,000 peptides, or peptoids unlikely toclosely mimic antigens. Array based approaches are presently limited tosmall collections of organisms with small proteomes (e.g., viruses)[10]. For peptide arrays, their relatively low peptide sequencediversity limits their ability to find individual sequences and motifsthat mimic the bona-fide antigen targeted by an antibody.

A principle advantage of the invention provided herein is that it isunbiased—that is, it does not assume which organisms are antigenic. Themethod claimed can identify epitopes in any organisms in the rapidlygrowing protein database, not just pre-specified viruses [10], allowingantigen identification within even the largest proteomes (e.g., wheatgenome=17 GB). Thus, the wheat genome alone is 100-1000× larger than thecombined genomes of all known human viruses.

SUMMARY

The following embodiments and aspects thereof are described andillustrated in conjunction with systems, compositions and methods whichare meant to be exemplary and illustrative, not limiting in scope.

In an aspect, the invention provides a method of identifying a pluralityof peptides, comprising: a) providing a biological sample comprising aplurality of antibodies; b) contacting the biological sample with aplurality of peptides; and c) identifying members of the plurality ofpeptides that form complex members of the plurality of antibodies.

The biological sample may comprise a bodily fluid. Antibodies may befound in any bodily fluid. In some embodiments of the invention, thebodily fluid comprises peripheral blood, plasm, serum lymphatic fluid,sweat, saliva, mucus, or a derivative of any thereof.

In an embodiment, identifying members of the plurality of peptides thatform a complex with members of the plurality of antibodies comprisessequencing a nucleic acid that encodes the peptide. Any usefulsequencing method may be employed. For example, the sequencing maycomprise next generation sequencing (NGS), Sanger sequencing, real-timePCR, or pyrosequencing. However, NGS can provide billions of sequencesencoding peptides in a single experiment. The nucleic acid and peptidecan be coupled physically, thereby allowing sequencing of the nucleicacid to determine the sequence of the peptide encoded by the nucleicacid. Any useful DNA construct can be used. For example, the nucleicacid molecule may comprise deoxyribonucleic acid (DNA), ribonucleic acid(RNA), or a derivative of any thereof.

In some embodiments, each peptide is directly coupled to itscorresponding nucleic acid molecule. For example, the nucleic acid maybe bound to a protein complex that comprises the peptide, includingwithout limitation a ribosome display system. In another embodiment,each peptide is indirectly coupled to its corresponding nucleic acidmolecule. For example, the corresponding nucleic acid molecule may becontained within a vector that encodes the peptide. As desired, thevector may be configured to express the peptide. The vector can also becomprised in a host cell. In an embodiment, the host cell expresses thepeptide. The peptide may be expressed on the surface of the host cell.Appropriate display systems are available in the art or are providedherein. For example, the host cell can be a microbial cell, a bacterialcell, an E. coli cell, a eukaryotic cell, a yeast cell, or a mammaliancell.

The method of the invention may further comprise capturing members ofthe plurality of peptides that form a complex with members of theplurality of antibodies prior to identifying members of the plurality ofpeptides that form complex members of the plurality of antibodies (stepc). In an embodiment, the capturing comprises capturing thepeptide-bound members of the plurality of antibodies. The peptide-boundmembers of the plurality of antibodies may be captured to a substrate.Any useful substrate can be used. For example, the substrate can be aplanar surface, e.g., a plate well, or a plurality of microbeads (alsoreferred to as microparticles). The plurality of microbeads may beconfigured to facilitate capture as desired. For example, the microbeadsmay be magnetic or carry a label, including without limitation afluorescent label. The bound members of the plurality of antibodies canbe captured using a reagent that binds an antibody constant region. Forexample, the reagent can be Protein A, Protein G, Protein L and/or ananti-immunoglobulin antibody or aptamer. As desired, the reagent iscoupled to the substrate, thereby allowing capture of peptide-boundantibodies to the substrate.

In some embodiments, the method of the invention further comprisesfiltering the plurality of antibodies prior to contacting the biologicalsample with a plurality of peptides (step b). The filtering may comprisecontacting the plurality of antibodies with at least one reagentconfigured to deplete antibodies that bind to assay components otherthan the plurality of peptides. In an embodiment, the at least onereagent comprises a host cell as described herein, e.g., a host cellthat is configured to display members of the plurality of peptides. Thestep allows removal of antibodies that bind to the host cell itselfinstead of members of the plurality of peptides.

In another embodiment, the method of the invention further comprisesfiltering the plurality of peptides prior to contacting the biologicalsample with a plurality of peptides (step b). The filtering of theplurality of peptides may comprise contacting the plurality of peptideswith at least one reagent configured to deplete peptides that form acomplex with assay components other than the plurality of antibodies. Inan embodiment, the at least one reagent configured to deplete peptidescomprises Protein A, Protein G, Protein L, and/or an anti-immunoglobulinantibody or aptamer.

As desired, filtering or depletion of both the plurality of antibodiesand the plurality of peptides can be performed.

In some embodiments, the methods of the invention further comprisedetermining at least one peptide motif from the members of the pluralityof peptides identified in c) above. The determining may comprisealigning the sequences of the members of the plurality of peptidesidentified in c) above. The aligning may comprise using a computationalalignment algorithm. Such algorithms are known in the art or providedherein. For example, the MEME program may be used as described furtherbelow.

In an aspect, the invention provides a method of identifying at leastone peptide indicative of a phenotype in a biological sample comprising:a) identifying a plurality of peptides in the biological sampleaccording to the method of the invention as described above; b)comparing the presence or level of members of the plurality of peptidesidentified in (a) to a reference value; and c) identifying a peptidewith a presence or level that differs from the reference based on thecomparison in b), thereby identifying the at least peptide indicative ofthe phenotype. The reference value for each member of the plurality ofpeptides may comprise a presence or level of that member of theplurality of peptides in a control sample.

In another aspect, the invention provides a method of identifying atleast one peptide motif indicative of a phenotype in a biological samplecomprising: a) identifying at least one peptide motif in the biologicalsample according to the method of the invention as described above; b)comparing the presence or level of the at least one peptide motifidentified in step a) to a reference value; and c) identifying at leastone peptide motif with a presence or level that differs from thereference based on the comparison in b), thereby identifying the atleast one peptide motif indicative of the phenotype. The reference valuemay comprise a presence or level of the same peptide motif in a controlsample.

In still another aspect, the invention provides a method ofcharacterizing a phenotype in a biological sample comprising: a)identifying a plurality of peptides in the biological sample accordingto the method of the invention as described above; b) comparing thepresence or level of each member of the plurality of peptides identifiedin a) to a reference value; and c) identifying a peptide with a presenceor level that differs from the reference based on the comparison in b),thereby characterizing the phenotype. The reference value for eachmember of the plurality of peptides may comprise a presence or level ofthat member of the plurality of peptides in a control sample. In anembodiment, the biological sample is from a subject and the method isused to characterize the phenotype in the subject.

In yet another aspect, the invention provides a method of characterizinga phenotype in a biological sample comprising: a) identifying at leastone peptide motif in the biological sample according to the method ofthe invention as described above; b) comparing the presence or level ofthe at least one peptide motif identified in step a) to a referencevalue; and c) identifying at least one peptide motif with a presence orlevel that differs from the reference based on the comparison in b),thereby identifying the at least one peptide motif indicative of thephenotype. In an embodiment, the reference value comprises a presence orlevel of the same peptide motif in a control sample. In an embodiment,the biological sample is from a subject and the method is used tocharacterize the phenotype in the subject.

The control sample in the aspects above may have a different phenotypethan the biological sample. One of skill will appreciate that thecontrol sample can be chosen to facilitate identification of peptidesindicative of a phenotype or useful for characterizing a phenotype. Forexample, if the phenotype of interest is a medical condition, thecontrol may be a sample that does not have the same condition. Or if thephenotype of interest is a state of a medical condition, the control maybe a sample that has a different state of the condition. As stillanother example, if the phenotype of interest is exposure to anenvironmental insult or pathogen, the control may be a sample that hasnot been exposed to the environmental insult or pathogen.

In some embodiments of the methods of the invention, the phenotypecomprises a medical condition, e.g., a disease or disorder. Thecharacterizing may comprise a diagnosis, prognosis or theranosis of thedisease or disorder. The characterizing may comprise determining astage, grade, progression, severity, treatment regimen likely to bebeneficial or not, and/or treatment response of the disease or disorder.

The disease or disorder can be any disease or disorder having an immunecomponent. For the example, the disease or disorder may comprise aninfectious, autoimmune, parasitic, allergic, oncological, neurological,cardiovascular, pregnancy-related or endocrine disease or disorder. Insome embodiments, the disease or disorder comprises an infectiousdisease or an autoimmune disease. The disease, disorder, or infectioncan be celiac disease (CD), Sjogren's Syndrome (SS), systemic lupuserythematosis (SLE), Epstein-Barr virus (EBV), rhinovirus,cytomegalovirus (CMV), Streptococcus sp., human immunodeficiency virus(HIV), Haemophilus influenza, Borrelia burgdorferi, Babesia microti,Ehrlichia sp., Anaplasma sp., Trypanosoma cruzi, Leishmania sp., Taeniasolium, Toxocara canis, or Toxoplasma gondii. The disease or disordermay comprise a microbial infection, viral infection, bacterialinfection, protozoan infection, parasitic infection, or fungalinfection.

In one embodiment, the disease or disorder comprises celiac disease (CD)and the at least one peptide motif is selected from QXXXPF[PS]E (SEQ IDNO: 6), PF SEM (SEQ ID NO: 7), PFSEX[FW] (SEQ ID NO: 8), QPXXPFX[ED](SEQ ID NO: 4) or combinations thereof.

In another embodiment, the disease or disorder comprises Chagas diseaseand the at least one peptide motif is selected from Table. 1

In another embodiment, the disease or disorder comprises Lyme diseaseand the at least one peptide motif is selected from Table 2.

In another embodiment, the disease or disorder comprises Toxoplasmosisand the at least one peptide motif is selected from Table 3.

In another embodiment, the disease or disorder comprises Cysticercosisand the at least one peptide motif is selected from Table 4.

In another embodiment, the disease or disorder comprises primaryEpstein-Barr virus (EBV) infection (mononucleosis) and the at least onepeptide motif is selected from Table 5.

In another embodiment, the disease or disorder comprises Zika virusinfection and the at least one peptide motif is selected from Table 6 orTable 7.

In another embodiment, the disease or disorder comprises HumanImmunodeficiency virus (HIV) infection and the at least one peptidemotif is selected from Table 8.

In another embodiment, the disease or disorder comprises latentEpstein-Barr virus (EBV) infection and the at least one peptide motif isselected from Table 9.

In still another embodiment, the disease or disorder comprisesrhinovirus and the at least one peptide motif is selected from Table 10.

In yet another embodiment, the disease or disorder comprisescytomegalovirus (CMV) and the at least one peptide motif is selectedfrom Table 11.

In an embodiment, the disease or disorder comprises Streptococcusinfection and the at least one peptide motif is selected from Table 12.

In an embodiment, the disease or disorder comprises Leishmania infectionand the at least one peptide motif is selected from Table 13.

In an embodiment, the disease or disorder comprises Babesia infectionand the at least one peptide motif is selected from Table 14.

In an embodiment, the disease or disorder comprises Ehrlichia infectionand the at least one peptide motif is selected from Table 15.

In an embodiment, the disease or disorder comprises Anaplasma infectionand the at least one peptide motif is selected from Table 16.

In an embodiment, the disease or disorder comprises Toxocara canisinfection and the at least one peptide motif is selected from Table 17.

In another aspect, the invention provides a peptide comprising asequence in any of Tables 1-18. In a related aspect, the methodcomprises a composition comprising at least one such peptide.

One of skill will appreciate that the methods of the invention can beused to assess peptides and/or motifs characteristic of multiplephenotypes in a single experiment or assay.

In an aspect, the invention provides the use of at least one reagent tocarry out the method of the invention described herein. In a relatedaspect, the invention provides a kit comprising at least one reagent tocarry out the method. The at least one reagent can be any useful reagentthat can be used to carry out the subject methods. In some embodiments,the at least one reagent comprises at least one of at least one peptideprovided by the invention; a composition provided by the invention; apeptide library display system; an antibody binding agent; a primer set;or a depletion reagent. The peptide library display system may comprisean E. coli display system. In one embodiment, the peptide librarydisplay system comprises a naïve or random peptide library. Such a naïvelibrary can be used to screen a sample for peptides, motifs andpatterns. See, for example, FIG. 1 and related discussion. In otherembodiments, the peptide library display system is configured tocharacterize a phenotype. See, e.g., FIG. 2A and FIG. 2B and relateddiscussion.

Provided herein are methods for treating a disease in a subject in needthereof. In various embodiments, the methods include identifying adisease comprising identifying at least one peptide, at least onepeptide motif or a combination of one or more peptides and peptidemotifs indicative of a phenotype (for example, a disease or disorder) ina biological sample by the methods described herein and treating thedisease. In exemplary embodiments, treatments include but are notlimited to administration of effective amounts of therapeutic agents,prescribing life style changes (such as dietary changes and/or exercise)or combinations thereof.

In exemplary embodiments, the diseases include but are not limited to aninfectious, autoimmune, parasitic, allergic, oncological, neurological,cardiovascular, pregnancy-related or endocrine disease or disorder. Insome embodiments, the disease or disorder comprises an infectiousdisease or an autoimmune disease. The disease, disorder, or infectioncan be celiac disease (CD), Sjogren's Syndrome (SS), systemic lupuserythematosis (SLE), Epstein-Barr virus (EBV), rhinovirus,cytomegalovirus (CMV), Streptococcus sp., human immunodeficiency virus(HIV), Haemophilus influenza, Borrelia burgdorferi, Babesia microti,Ehrlichia sp., Anaplasma sp., Trypanosoma cruzi, Leishmania sp., Taeniasolium, Toxocara canis, or Toxoplasma gondii. The disease or disordermay comprise a microbial infection, viral infection, bacterialinfection, protozoan infection, parasitic infection, or fungalinfection. Treatments for each of the diseases and the effective amountsfor the treatments will be apparent to a person of skill in the art.

In one embodiment, the disease is celiac disease and exemplarytreatments include but are not limited to recommending gluten-free dietto the subject. Further treatments and effective dosages will beapparent to a person of skill in the art.

In another embodiment, the disease is Chagas disease and treatmentinclude but are not limited to administering an effective amount ofbenzimidazole, nifurtimox or combinations thereof. For heart-relatedcomplications of Chagas disease, treatments may include medications, apacemaker or other devices to regulate your heart rhythm, surgery, oreven a heart transplant. For digestive-related complications of Chagasdisease, treatments may include diet modification, medications,corticosteroids or, in severe cases, surgery. Further treatments andeffective dosages will be apparent to a person of skill in the art.

In a further embodiment the disease is Lyme disease. In someembodiments, the subject diagnosed with Lyme disease is treated withtherapeutically effective amounts of appropriate antibiotics (forexample, doxycycline, amoxicillin, or cefuroxime axetil). Patients withcertain neurological or cardiac forms of Lyme disease may requireintravenous treatment with drugs such as ceftriaxone or penicillin.Further treatments and effective dosages will be apparent to a person ofskill in the art.

In an embodiment, the disease is Toxoplasma gondii infection. In someembodiments, the subjects diagnosed with Toxoplasma gondii are treatedwith pyrimethamine and sulfadiazine, plus folinic acid. Furthertreatments and effective dosages will be apparent to a person of skillin the art.

In one embodiment, the disease is a Taenia solium infection(Cysticercosis). In some embodiments, the subjects diagnosed withCysticercosis are treated with praziquantel (Biltricide), niclosamide,albendazole (Albenza) or combinations thereof. Further treatments andeffective dosages will be apparent to a person of skill in the art.

In another embodiment, the disease is mononucleosis by EBV infection. Insome embodiments, treatments for mononucleosis by EBV infection includerest, fluid and anti-viral agents such including acyclovir, ganciclovirand/or foscarnet. Further treatments and effective dosages will beapparent to a person of skill in the art.

In an embodiment, the disease is a Zika virus infection. In exemplaryembodiments, treatment for Zika virus infection includes rest and fluidsand acetaminophen or paracetamol. Further treatments and effectivedosages will be apparent to a person of skill in the art.

In one embodiment, the disease is an HIV infection. In exemplaryembodiments, the treatment for HIV includes antiretroviral therapy.Further treatments and effective dosages will be apparent to a person ofskill in the art.

In an embodiment, the disease is Sjogren's syndrome. In exemplaryembodiments, the treatment for Sjogren's syndrome includes pilocarpine,cevimeline, NSAIDS, Hydroxychloroquine or combinations thereof. Furthertreatments and effective dosages will be apparent to a person of skillin the art.

In one embodiment, the disease is a Rhinovirus infection. In exemplaryembodiments, the treatment for rhinovirus infections include rest,hydration, antihistamines, and nasal decongestants and in case offurther bacterial infection, antibacterial agents. Further treatmentsand effective dosages will be apparent to a person of skill in the art.

In an embodiment, the disease is a Cytomegalovirus infection. Inexemplary embodiments, treatments for Cytomegalovirus infections includevalganciclovir ganciclovir foscarnet, cidofovir or maribavir. Furthertreatments and effective dosages will be apparent to a person of skillin the art.

In some embodiments, the disease is a bacterial infections (for example,Streptococcus sp. infection, Borrelia infection, Ehrlichia infection,Anaplasma infection, Haemophilus influenza infection or Babesiainfection). In exemplary embodiments, treatment for bacterial infectionsinclude antibacterial agents such a antibiotics, cephalosporinantibiotics, macrolide antibiotics, penicillin antibiotics, quinoloneantibiotics, sulphonamide antibiotics, tetracycline antibiotics orcombinations thereof. Further treatments and effective dosages will beapparent to a person of skill in the art.

All publications, patents, and patent applications mentioned in thisspecification are herein incorporated by reference to the same extent asif each individual publication, patent, or patent application wasspecifically and individually indicated to be incorporated by reference.

BRIEF DESCRIPTION OF THE DRAWINGS

Exemplary embodiments are illustrated in referenced figures. It isintended that the embodiments and figures disclosed herein are to beconsidered illustrative rather than restrictive. The novel features ofthe invention are set forth with particularity in the appended claims. Abetter understanding of the features and advantages of the presentinvention will be obtained by reference to the following detaileddescription that sets forth illustrative embodiments, in which theprinciples of the invention are utilized, and the accompanying drawingsof which:

FIG. 1 illustrates an overview of a method of identifying in a sample,which can be used for peptide motif or pattern discovery.

FIG. 2A illustrates an overview of a method of determining an antibodyspecificity in a subject or individual. FIG. 2B illustrates an overviewof a method of characterizing a phenotype in a subject or individual,e.g., to provide a diagnosis of a condition such as a disease orinfection in the individual.

FIG. 3 illustrates a method of diagnosing a subject as having Celiacdisease. The method includes i) enriching a collection of antibodybinding peptides from a random peptide library of 6-60 amino acids forbinding to a biological sample, ii) isolating plasmid DNA from theenriched library, iii) subjecting the amplicon library to sequencing(NGS), iii) counting the enrichment of a motif previously validated tobe both sensitive and specific for celiac disease (e.g. QPXXPFX[DE] (SEQID NO: 4)), and comparing this enrichment to a reference value orthreshold value.

FIG. 4A illustrates the method and workflow to develop multiplexeddiagnostic motif panels. FIG. 4B illustrates the how multiple motifpanels can be used to simultaneously diagnose multiple differentdiseases.

FIG. 5 illustrates the sum of z-scores (Standardized enrichment) for afour motif panel for Celiac disease discovery and validation samples.

FIG. 6 illustrates the performance of Trypanosoma cruzi infection(Chagas disease) motif panel in a discovery and validation sample sets,exhibiting a sensitivity of 100% and specificity of 100% in thevalidation set.

FIG. 7 illustrates the performance of Borrelia burgdorferi infectionmotif panel in a discovery and validation sets of early, earlydisseminated, and late Lyme disease, exhibiting a sensitivity of 97% andspecificity of 99.8%.

FIG. 8 illustrates the performance of an acute Toxoplasma gondiiinfection motif panel in a discovery sample set, exhibiting asensitivity of 100% and specificity of 100%.

FIG. 9 illustrates the performance of (chronic or acute) Toxoplasmagondii infection motif panel in a discovery sample set, exhibiting asensitivity of 100% and specificity of 100%.

FIG. 10 illustrates the performance of Taenia solium (Cysticercosis)infection motif panel in a discovery sample set, exhibiting asensitivity of >95%% and specificity of 99.5%.

FIG. 11A illustrates the performance of an Esptein Barr VirusMononucleosis infection motif panel in a discovery and validation samplesets, exhibiting a sensitivity of 90% and specificity of 99%. FIG. 11Billustrates the utility of the absence of motif enrichment in a sample,that is specific for Epstein Barr virus infection.

FIG. 12A illustrates the performance of IgG ZIKA virus infection motifpanel in a discovery sample set. FIG. 12B illustrates the performance ofan IgM motif panel for diagnosis of Zika virus infection, exhibiting asensitivity of 95% and specificity of 100%.

FIG. 13 illustrates the performance of HIV infection motif panel in adiscovery and validation sample sets, exhibiting a sensitivity of 100%and specificity of 100%.

FIG. 14 illustrates the performance of an individual Sjogren's syndromediagnostic motif in a discovery and validation sample sets.

FIG. 15 illustrates the performance of Leishmania infection motif panelin a discovery and validation sample sets, exhibiting a sensitivity of65% and specificity of 100%.

FIG. 16 illustrates the performance of Babesia infection motif panel ina discovery and validation sample sets, exhibiting a specificity of>99.5%.

FIG. 17 illustrates the performance of Ehrlichia infection motif panelin a discovery and sample set.

FIG. 18 illustrates the performance of Anaplasma phagocytophiliuminfection motif panel in a discovery sets, exhibiting a specificity of>99.5%.

FIG. 19 illustrates the performance of a Toxocara canis infection motifpanel in a discovery sample set, exhibiting a specificity of >99.5%.

FIG. 20: Percentage of subjects with fold enrichment of depletionreagent motifs in HASRD (n=358 subjects).

FIG. 21 illustrates that the depletion reagent and method effectivelyremoves antibodies from serum prior to screening. Three separate motifsare shown. On each graph, first 3 bars represent the enrichment valuefor the given motif in 3 separate patients after standard depletion. Thesecond three bars are the enrichment values for the same 3 patientsafter depletion with the depletion reagent.

FIG. 22: The depletion reagent removed 80-90% of antibodies associatedwith 11 motifs for each patient. The enrichment for each motif wasdetermined on sera that had been processed for display seq using bothdepletion methods. The percent decrease for each motif after treatmentwith the depletion reagent was calculated. All motifs included in theanalysis were known to be present in the depletion reagent.

FIG. 23: The depletion reagent reduces reactivity of serum to the X12library by 5-10 fold. The results are the average and standard deviationof 5 serum samples. The reactivity of the serum samples to the eCPXscaffold only represents background binding of serum in the absence ofpeptides.

FIG. 24: Two motifs that were not present in the depletion reagentdemonstrate increased enrichment in serum treated with the depletionreagent as compared with eCPX depleted sera. Three serum samples areshown and each was run in duplicate. The depletion reagent enhancesenrichment by ˜3 fold as compared with standard depletion.

DETAILED DESCRIPTION OF THE INVENTION

All references cited herein are incorporated by reference in theirentirety as though fully set forth. Unless defined otherwise, technicaland scientific terms used herein have the same meaning as commonlyunderstood by one of ordinary skill in the art to which this inventionbelongs. Allen et al., Remington: The Science and Practice of Pharmacy22nd ed., Pharmaceutical Press (Sep. 15, 2012); Hornyak et al.,Introduction to Nanoscience and Nanotechnology, CRC Press (2008);Singleton and Sainsbury, Dictionary of Microbiology and MolecularBiology 3rd ed., revised ed., J. Wiley & Sons (New York, N.Y. 2006);Smith, March's Advanced Organic Chemistry Reactions, Mechanisms andStructure 7th ed., J. Wiley & Sons (New York, N.Y. 2013); Singleton,Dictionary of DNA and Genome Technology 3rd ed., Wiley-Blackwell (Nov.28, 2012); and Green and Sambrook, Molecular Cloning: A LaboratoryManual 4th ed., Cold Spring Harbor Laboratory Press (Cold Spring Harbor,N.Y. 2012), provide one skilled in the art with a general guide to manyof the terms used in the present application. For references on how toprepare antibodies, see Greenfield, Antibodies A Laboratory Manual 2nded., Cold Spring Harbor Press (Cold Spring Harbor N.Y., 2013); Köhlerand Milstein, Derivation of specific antibody-producing tissue cultureand tumor lines by cell fusion, Eur. J. Immunol. 1976 July, 6(7):511-9;Queen and Selick, Humanized immunoglobulins, U.S. Pat. No. 5,585,089(1996 December); and Riechmann et al., Reshaping human antibodies fortherapy, Nature 1988 Mar. 24, 332(6162):323-7.

One skilled in the art will recognize many methods and materials similaror equivalent to those described herein, which could be used in thepractice of the present invention. Other features and advantages of theinvention will become apparent from the following detailed description,taken in conjunction with the accompanying drawings, which illustrate,by way of example, various features of embodiments of the invention.Indeed, the present invention is in no way limited to the methods andmaterials described. For convenience, certain terms employed herein, inthe specification, examples and appended claims are collected here.

Unless stated otherwise, or implicit from context, the following termsand phrases include the meanings provided below. Unless explicitlystated otherwise, or apparent from context, the terms and phrases belowdo not exclude the meaning that the term or phrase has acquired in theart to which it pertains. The definitions are provided to aid indescribing particular embodiments, and are not intended to limit theclaimed invention, because the scope of the invention is limited only bythe claims. Unless otherwise defined, all technical and scientific termsused herein have the same meaning as commonly understood by one ofordinary skill in the art to which this invention belongs.

The invention provides compositions and methods that can be used todetect the presence of an antibody specificity in a biological samplecontaining a mixture of antibodies. The method may comprise measuringthe enrichment of specific peptide motifs in a set of thousands or more,e.g., at least 10⁵ peptides, that bind to antibodies present in thesample. The method of the invention may be referred to herein as“Display-seq.”

As used herein, “specificity” can refer to an antibody species thatbinds to particular antigen, or a peptide motif pattern, or sequencecontaining an antibody's preferred amino acid contact residues.

The invention further provides a method to discover amino acid sequencemotifs (“motifs”), which, when enriched within a sample dataset, can beused to characterize a phenotype. As an example, the phenotype may be adisease or disorder and the characterization can include a diagnosis,prognosis or theranosis for the disease or disorder. In an embodiment,the method is used to detect a disease in an individual by determiningmotifs present in the individual. The invention enables the facilediscovery of synthetic peptide compositions that enable detection ofantibodies in a mixture.

The invention further provides amino acid sequence motifs and syntheticpeptide compositions useful for detecting antigen-specific antibodiespresent within a sample. The presence of antigen specific antibodies canbe indicative or diagnostic of disease or disorder, e.g., an infection.Thus, in various embodiments, the compositions and methods of theinvention are used for diagnosing human disease, for assessing vaccineefficacy and safety, or for monitoring changes in immune status. Theinvention may overcome limitations of diagnostic methods utilizingisolated biochemical reagents. For example, the invention does notrequire experimental optimization of a single reagent, it allows forarbitrary combinations of motifs to be used to make diagnosticdecisions, and it allows for measurement of a large number of motifenrichments with a single data set, thereby seamlessly integrating manydifferent biological assays into one process.

The compositions and methods of the invention are described furtherbelow. Briefly, a random peptide library is co-incubated with a samplethat contains a mixture of different antibodies. Peptide library membersthat capture antibodies are then recovered. The sequences of allpeptides in the enriched library of binders are then determined, therebyproviding a signature of antibody specificities in the sample. Thepeptide library may be displayed on the surface of a biological entitythat comprises a nucleic acid sequence encoding the peptide. Theidentity of peptides that were bound by antibodies can be determined bysequencing the nucleic acids. In some embodiments, the sequencingcomprises massively parallel DNA sequencing or next generationsequencing (NGS). Analysis of peptide signatures and antibodyspecificities in a sample can be used to characterize a phenotype, suchas providing a diagnosis, prognosis or theranosis of a disease ordisorder.

Definitions

As used herein the term “comprising” or “comprises” is used in referenceto compositions, methods, and respective component(s) thereof, that areuseful to an embodiment, yet open to the inclusion of unspecifiedelements, whether useful or not. It will be understood by those withinthe art that, in general, terms used herein are generally intended as“open” terms (e.g., the term “including” should be interpreted as“including but not limited to,” the term “having” should be interpretedas “having at least,” the term “includes” should be interpreted as“includes but is not limited to,” etc.).

Unless stated otherwise, the terms “a” and “an” and “the” and similarreferences used in the context of describing a particular embodiment ofthe application (especially in the context of claims) can be construedto cover both the singular and the plural. The recitation of ranges ofvalues herein is merely intended to serve as a shorthand method ofreferring individually to each separate value falling within the range.Unless otherwise indicated herein, each individual value is incorporatedinto the specification as if it were individually recited herein. Allmethods described herein can be performed in any suitable order unlessotherwise indicated herein or otherwise clearly contradicted by context.The use of any and all examples, or exemplary language (for example,“such as”) provided with respect to certain embodiments herein isintended merely to better illuminate the application and does not pose alimitation on the scope of the application otherwise claimed. Theabbreviation, “e.g.” is derived from the Latin exempli gratia, and isused herein to indicate a non-limiting example. Thus, the abbreviation“e.g.” is synonymous with the term “for example.” No language in thespecification should be construed as indicating any non-claimed elementessential to the practice of the application.

“Beneficial results” may include, but are in no way limited to,lessening or alleviating the severity of the disease condition,preventing the disease condition from worsening, curing the diseasecondition, preventing the disease condition from developing, loweringthe chances of a patient developing the disease condition and prolonginga patient's life or life expectancy. Beneficial or desired clinicalresults include, but are not limited to, alleviation of one or moresymptom(s), diminishment of extent of the deficit, stabilized (i.e., notworsening) state of progression, delay or slowing of progression orinvasiveness, and amelioration or palliation of symptoms associated withthe brain insulin resistance. Treatment also includes a decrease inmortality or an increase in the lifespan of a subject as compared to onenot receiving the treatment.

As used herein, the terms “treat,” “treatment,” “treating,” or“amelioration” refer to therapeutic treatments, wherein the object is toreverse, alleviate, ameliorate, inhibit, slow down or stop theprogression or severity of a condition associated with, a disease ordisorder. The term “treating” includes reducing or alleviating at leastone adverse effect or symptom of a condition, disease or disorderdescribed herein. Treatment is generally “effective” if one or moresymptoms or clinical markers are reduced. Alternatively, treatment is“effective” if the progression of a disease is reduced or halted. Thatis, “treatment” includes not just the improvement of symptoms ormarkers, but also a cessation of at least slowing of progress orworsening of symptoms that would be expected in absence of treatment.Beneficial or desired clinical results include, but are not limited to,alleviation of one or more symptom(s), diminishment of extent ofdisease, stabilized (i.e., not worsening) state of disease, delay orslowing of disease progression, amelioration or palliation of thedisease state, and remission (whether partial or total), whetherdetectable or undetectable. The term “treatment” of a disease alsoincludes providing relief from the symptoms or side-effects of thedisease (including palliative treatment).

As used herein, the term “administering,” refers to the placement anagent as disclosed herein into a subject by a method or route whichresults in at least partial localization of the agents at a desiredsite.

As used herein, the term “amino acid” refers to naturally occurring andsynthetic amino acids, as well as amino acid analogs and amino acidmimetics that function in a manner similar to the naturally occurringamino acids. Naturally occurring amino acids are those encoded by thegenetic code, as well as those amino acids that are later modified,e.g., hydroxyproline, -carboxyglutamate, and O-phosphoserine. Amino acidanalogs refers to compounds that have the same basic chemical structureas a naturally occurring amino acid, i.e., an carbon that is bound to ahydrogen, a carboxyl group, an amino group, and an R group, e.g.,homoserine, norleucine, methionine sulfoxide, methionine methylsulfonium. Such analogs have modified R groups (e.g., norleucine) ormodified peptide backbones, but retain the same basic chemical structureas a naturally occurring amino acid. Amino acid mimetics refers tochemical compounds that have a structure that is different from thegeneral chemical structure of an amino acid, but that functions in amanner similar to a naturally occurring amino acid. Amino acids may bereferred to herein by either their commonly known three letter symbolsor by the one-letter symbols recommended by the IUPAC-IUB BiochemicalNomenclature Commission. Nucleotides, likewise, may be referred to bytheir commonly accepted single-letter codes.

A protein refers to any of a class of nitrogenous organic compounds thatconsist of large molecules composed of one or more long chains of aminoacids and are an essential part of all living organisms. A protein maycontain various modifications to the amino acid structure such asdisulfide bond formation, phosphorylations and glycosylations. A linearchain of amino acid residues may be called a “polypeptide.” A proteincontains at least one polypeptide. Short polypeptides, e.g., containingless than 20-30 residues, are sometimes referred to as “peptides.” Theterms protein, polypeptide and peptide may be used interchangeablyherein to refer to molecules comprised of amino acid residues.

An antibody (Ab), also known as an immunoglobulin (Ig), is a large,Y-shape protein produced by plasma cells that is used by the immunesystem to identify and neutralize pathogens such as bacteria andviruses. The antibody recognizes a unique molecule of the agent, calledan antigen, via the antibody's so-called variable region[11].

The term “autoantibody” as used herein refers to an antibody produced bythe immune system in an organism in response to, and directed against, aconstituent of its own tissues. Many autoimmune diseases and disorders,e.g., lupus erythematosus, celiac disease and type 1 diabetes, arecaused by such autoantibodies wherein the immune system fails toproperly distinguish between “self” and “non-self.”

The term “motif” as used herein comprises an amino acid sequencepattern, which comprises preferred amino acids at each position of apeptide sequence. For example, [DE]TX[FYL]K (SEQ ID NO: 1) where “K” isany amino acid and each letter corresponds to the conventionalone-letter amino acid code. The notation [XYZ] within a motif means thatthe indicated position comprises one amino acid that is selected from “Xor Y or Z”. Motifs may alternatively be presented graphically as asequence “logo,” wherein the frequencies of occurrence of individualamino acids at each position in a motif are represented by the height ofthe character (e.g. one letter amino acid code) at that position. Alarger letter indicates a higher frequency of occurrence. Examples areshown in FIG. 1 and FIG. 3 herein.

The term “pattern” refers to a sequence of amino acids, wherein thesequence may vary in length and may have intervening random amino acids.For example, DTXFK (SEQ ID NO: 2) and DXTXFXXK (SEQ ID NO: 3) arepatterns.

The term “specificity repertoire” as used herein comprises the set ofall binding specificities, (e.g. motifs, peptides, or patterns)comprised within an antibody repertoire.

The term “epitope” refers to the part of an antigen molecule/s to whichan antibody attaches itself. For example, in the case of a proteinantigen, the epitope can be the amino acid sequence or proteinstructural region to which an antibody binds.

The term “epitope repertoire” as used herein comprises the set of allantigens recognized, or bound by, by antibodies within a sample, orgroup of samples. For example, the epitope repertoire may refer to theset of all peptides or antigens recognized, or bound by, by antibodieswithin a sample, or group of samples.

The term “enrichment” as used herein refers to the number ofobservations of a peptide, pattern, or motif within an epitoperepertoire divided by the number expected within a random dataset ofequivalent size. For example, in a hypothetical 9-mer peptide library(-XXXXXXXXX-, where X is any amino acid, the pattern QPXXPFX[ED] (SEQ IDNO: 4) is expected to occur once in every 800,000((1aa/20aa)⁴×(2aa/20aa)×2) random sequences (aa=amino acid). If 4million sequences were determined, then one would expect to observe five(5) occurrences (i.e., once in every 800,000 sequences). As an example,if the pattern was actually observed in 50 unique peptides sequences(i.e. 50 observations) in an epitope repertoire, then the pattern wouldbe “enriched” by 10-fold versus random.

The term “threshold” as used herein refers to the magnitude or intensitythat must be exceeded for a certain reaction, phenomenon, result, orcondition to occur or be considered relevant. For example, the thresholdcan be a numerical value above which enrichment is considered relevant.The relevance can depend on context, e.g., it may refer to a positive,reactive or statistically significant relevance.

The term “peptide display library” as used herein refers to any one of afamily of methods wherein a sequence of amino acids is physicallyassociated with a nucleic acid sequence that encodes that peptide. See[12].

The term “peptide signature” as used herein refers to the antigenicpeptide repertoire detected in a sample. A peptide signature maycomprise the enrichment of various peptides and/or common motifsobserved in the sample

The term “ELISA” as used herein refers to an enzyme-linked immunosorbentassay, which is a wet-lab test that uses antibodies and color change toidentify a substance. Methods of performing ELISA assays are known tothose of skill in the art. Typically, antigens from a sample areattached to a surface, such as the well of an ELISA plate. Then, afurther specific antibody is applied over the surface so it can bind tothe antigen. This antibody is linked to an enzyme, and, in the finalstep, a substance containing the enzyme's substrate is added. Thesubsequent reaction produces a detectable signal, most commonly a colorchange in the substrate. The amount of color produced can correlate withthe amount of antigen in the sample. The immunoassay format may bemodified to use detection systems other than enzyme-mediated colorchange, e.g., radioactivity or fluorescence. The term “RIA” as usedherein refers to a radioimmunoassay, “MIA” as used herein refers to amagneticimmunoassay, and “ECL” as used herein refers to enzymaticchemiluminescence.

The term “depleted sample” as used herein refers to specimen containinga mixture of antibodies wherein certain species of antibodies have beenremoved from the sample, for example by affinity capture. Depletedsamples include those that have been incubated with a subset of thedisplay library (e.g., phage/bacteria/yeast) to remove antibody speciesthat bind to members of the library subset. The library subset could bea single clone that displays the scaffold used to present the peptide onthe particle/cell surface or a mixture of two or more cell types thatdisplay different peptides that bind to antibodies of known specificityin the sample.

The term “computational depletion” as used herein refers to the removalof peptides from a set of peptides sequences that contain one or morespecified motifs. For example, the motif QPXXPFX[DE] (SEQ ID NO: 4), asspecified, would remove all instances of peptides in a large set ofpeptides that contain this motif thereby computationally depleting theset of peptides carrying an instance of this motif. Many known orabundant motifs can be used to define a set of motifs for depletion.Depletion of common motifs has the effect of enriching rare motifs.

The term “clustering algorithm” as used herein refers to a computationalalgorithm used to perform “cluster analysis.” Cluster analysis orclustering is the task of grouping a set of objects in such a way thatobjects in the same group (called a cluster) are more similar (in somesense or another) to each other than to those in other groups(clusters). A variety of clustering algorithms are known to those ofskill in the art. See, e.g., [13-15].

The terms “identical” or percent “identity,” in the context of two ormore nucleic acids or polypeptide sequences, refer to two or moresequences or subsequences that are the same or have a specifiedpercentage of amino acid residues or nucleotides that are the same(i.e., about 60% identity, e.g., 65%, 70%, 75%, 80%, 85%, 90%, 91%, 92%,93%, 94%, 95%, 96%, 97%, 98%, 99%, or higher identity over a specifiedregion, when compared and aligned for maximum correspondence over acomparison window or designated region) as measured using acomputational alignment algorithm. Such sequences are then said to be“substantially identical.” For sequence comparison, typically onesequence acts as a reference sequence, to which test sequences arecompared. When using a sequence comparison algorithm, test and referencesequences are entered into a computer, subsequence coordinates aredesignated, if necessary, and sequence algorithm program parameters aredesignated. Default program parameters can be used, or alternativeparameters can be designated. The sequence comparison algorithm thencalculates the percent sequence identities for the test sequencesrelative to the reference sequence, based on the program parameters. Acommon example of an algorithm that is suitable for determining percentsequence identity and sequence similarity are the BLAST and BLAST 2.0algorithms, which are described in Altschul et al., Nuc. Acids Res.25:3389-3402 (1977) and Altschul et al., J. Mol. Biol. 215:403-410(1990).

A “comparison window,” as used herein, includes reference to a segmentof any one of the number of contiguous positions may be compared to areference sequence of the same number of contiguous positions after thetwo sequences are optimally aligned. Methods of alignment of sequencesfor comparison are well-known in the art. Optimal alignment of sequencesfor comparison can be conducted, e.g., by the local homology algorithmof Smith & Waterman, Adv. Appl. Math. 2:482 (1981), by the homologyalignment algorithm of Needleman & Wunsch, J. Mol. Biol. 48:443 (1970),by the search for similarity method of Pearson & Lipman, Proc. Nat'l.Acad. Sci. USA 85:2444 (1988), by computerized implementations of thesealgorithms (GAP, BESTFIT, FASTA, and TFASTA in the Wisconsin GeneticsSoftware Package, Genetics Computer Group, 575 Science Dr., Madison,Wis.), or by manual alignment and visual inspection (see, e.g., CurrentProtocols in Molecular Biology (Ausubel et al., eds. 1995 supplement)).

The term “triplet-phosphoramidite” refers to a synthetic molecule ofdeoxyribonucleic acid (DNA) composed of three nucleotide bases. See,e.g., (Onto A, 1995), (Kayushin et al., 1996).

The term “surface display” as used herein refers to the presentation ofheterologous peptides and proteins on the outer surface of a biologicalparticle such as living cell, virus, or bacteriophage. See [16].

The terms “body fluid” or “bodily fluids” are liquids originating frominside the bodies of organisms. Bodily fluids include amniotic fluid,aqueous humour, vitreous humour, bile, blood (e.g., serum), breast milk,cerebrospinal fluid, cerumen (earwax), chyle, chyme, endolymph andperilymph, exudates, feces, female ejaculate, gastric acid, gastricjuice, lymph, mucus (e.g., nasal drainage and phlegm), pericardialfluid, peritoneal fluid, pleural fluid, pus, rheum, saliva, sebum (skinoil), serous fluid, semen, smegma, sputum, synovial fluid, sweat, tears,urine, vaginal secretion, and vomit. Extracellular bodily fluids includeintravascular fluid (blood plasma), interstitial fluids, lymphatic fluidand transcellular fluid. Immunoglobulin G (IgG), the most abundantantibody subclass, may be found in all body fluids. “Biological sample”also includes a mixture of the above-mentioned body fluids. “Biologicalsamples” may be untreated or pretreated (or pre-processed) biologicalsamples.

The term “disease” refers to an abnormal condition affecting the body ofan organism. The term “disorder” refers to a functional abnormality ordisturbance. The terms disease or disorder are used interchangeablyherein unless otherwise noted or clear given the context in which theterm is used. The terms disease and disorder may also be referred tocollectively as a “condition.”

The term “phenotype” as used herein comprises the composite of anorganism's observable characteristics or traits, such as its morphology,development, biochemical or physiological properties, phenology,behavior, and products of behavior.

The term “diagnosis,” or “dx,” refers to the identification of thenature and cause of a certain phenomenon. As used herein, a diagnosistypically refers to a medical diagnosis, which is the process ofdetermining which disease or condition explains a symptoms and signs. Adiagnostic procedure, often a diagnostic test or assay, can be used toprovide a diagnosis. A diagnosis can comprise detecting the presence ofa disease or disorder, or

The term “prognosis,” or “px,” as used herein refers to predicting thelikely outcome of a current standing. For example, a prognosis caninclude the expected duration and course of a disease or disorder, suchas progressive decline or expected recovery.

The term “theranosis,” or “tx” as used herein refers to a diagnosis orprognosis used in the context of a medical treatment. For example,theranostics can include diagnostic testing used for selectingappropriate and optimal therapies (or the inverse) based on the contextof genetic content or other molecular or cellular analysis. Theranosticsincludes pharmacogenomics, personalized and precision medicine.

As used here, the terms “massively parallel signature sequencing” (MPSS)or “next generation sequencing” (NGS) and the like are usedinterchangeably to refer to high throughput nucleic acid sequencing(HTS) approaches. Platforms for NGS that rely on different sequencingtechnologies are commercially available from a number of vendors such asPacific Biosciences, Ion Torrent from Thermo Fisher, 454 Life Sciences,Illumina, Inc. (e.g., MiSeq, NextSeq, HiSeq) and Oxford Nanopore. Forreview of NGS technologies, see, e.g., van Dijk E L et al. Ten years ofnext-generation sequencing technology. Trends Genet. 2014 September;30(9):418-26. [17]

General molecular biology terminology and techniques are known to thoseof skill in the art. See, e.g., Sambrook et al., Molecular Cloning: ALaboratory Manual, Cold Spring Harbor Press, N.Y., (3.sup.rd ed., 2000);and Brent et al., Current Protocols in Molecular Biology, John Wiley &Sons, Inc. (ringbou ed., 2003).

Phenotypes

As described herein, the compositions and methods of the invention maybe used to characterize a phenotype in a sample of interest. Thephenotype can be any phenotype of interest that may be characterizedusing the subject compositions and methods. Consider a non-limitingexample wherein the phenotype comprises a disease or disorder. In suchcases, the characterizing may be providing a diagnosis, prognosis ortheranosis for the disease or disorder. In an illustrative embodiment, asample from a subject is analyzed using the compositions and methods ofthe invention. The analysis is then used to predict or determine thepresence, stage, grade, outcome, or likely therapeutic response of adisease or disorder in the subject. The analysis can also be used toassist in making such prediction or determination.

The repertoire of antibodies present in an organism can be indicative ofvarious antigens that the organism has encountered. Such antigens may bederived from external insults, e.g., viral particles or microorganismssuch as bacterial cells or fungi. External insults may also be allergenssuch as pollen or gluten, or environmental factors such as toxins. Anorganism may also generate antibodies specific to internal antigens. Forexample, autoimmune disorders are caused by the formation of antibodiesthat recognize antigens of the host organism. Autoantibodies to variouscancer antigens have been observed. In sum, a host organism can compriseantibodies to numerous external and internal antigens indicative of amultitude of diseases, disorders and other environmental factors. Thus,the compositions and methods of the invention can be used tocharacterize any number of phenotypes in an organism, including withoutlimitation determining environmental exposures and/or providing adiagnosis, prognosis or theranosis for various medical conditions. Theseconditions include without limitation infectious, autoimmune, parasitic,allergic, neoplastic, genetic, oncological, neurological,cardiovascular, and endocrine diseases and disorders.

Method to Discover Epitopes and Motifs Recognized by a Mixture ofAntibodies in a Sample

The present invention enables the discovery and identification of aminoacid sequence motifs and peptide epitopes that are bound by antibodieswithin a sample that contains a mixture of antibodies. Thus, the methodcan provide a peptide signature for the sample. In an embodiment, thesample comprises a bodily fluid as a source of the mixture ofantibodies.

An outline of one embodiment of the method is shown in FIG. 1. A peptidelibrary is contacted with a desired number (n) of antibody (Ig)containing sample(s) 101. Each member of the peptide library can bedisplayed on the surface of a host cell. The sample(s) can be from oneor more individual with a known phenotype of interest, including withoutlimitation a disease or infection. This can allow the identification ofpeptides in the individuals indicative of the phenotype. In a next step102, library members binding Ig (e.g., peptide binders) in the n samplesare separated from non-binders. In this step, the peptides which arebound by antibodies from the sample are identified. The identity of thebound peptides is determined by isolating DNA encoding each peptide fromthe separated sublibraries of Ig binders (n times) 103. The DNA can bewithin a vector, e.g., a plasmid, which encodes the peptide. Thesequences of the DNAs encoding the displayed peptides (e.g NGS of namplicon libraries) are translated into the encoded peptide sequences104. This step thereby provides the peptide signature of the sample. Asdesired, the peptide sequences present in the peptide sets (epitoperepertoires), but absent from, or less prominent in peptide sets fromcontrol samples are determined 105. As an example, the individual/s mayhave a certain disease whereas the control samples are from individualswithout the disease. This arrangement may be used to identifydisease-specific peptide sets. Further as desired, motif discovery(sequence clustering) is performed using resulting set of the peptides106. Following the above example, these motifs may comprise diseasespecific motifs that can be used to characterize (e.g., provide adiagnosis, prognosis or theranosis) of the disease. The Examples hereinprovide a number of such motifs identified using the methods of theinvention for various disease settings.

In an aspect, the invention provides a method of identifying a pluralityof peptides, comprising: a) providing a biological sample comprising aplurality of antibodies; b) contacting the biological sample with aplurality of peptides; and c) identifying members of the plurality ofpeptides that form a complex members of the plurality of antibodies.

The biological sample may comprise a bodily fluid. Antibodies may befound in any bodily fluid. In some embodiments of the invention, thebodily fluid comprises peripheral blood, lymphatic fluid, sweat, saliva,mucus, or a derivative of any thereof.

In an embodiment, identifying members of the plurality of peptides thatform a complex with members of the plurality of antibodies comprisessequencing a nucleic acid that encodes the peptide. Any usefulsequencing method may be employed. For example, the sequencing maycomprise next generation sequencing (NGS), Sanger sequencing, real-timePCR, or pyrosequencing. Next generation sequencing can allow screening avast number of sequencing in a single experiment. The nucleic acid andpeptide can be coupled, thereby allowing sequencing of the nucleic acidto be converted to the sequence of the peptide. Any useful DNA constructcan be used. For example, the nucleic acid molecule may comprisedeoxyribonucleic acid (DNA), ribonucleic acid (RNA), or a derivative ofany thereof.

In some embodiments, each peptide is directly coupled to itscorresponding nucleic acid molecule. For example, the nucleic acid maybe bound to a protein complex that comprises the peptide, includingwithout limitation a ribosome, mRNA, or DNA display system. In anotherembodiment, each peptide is indirectly coupled to its correspondingnucleic acid molecule. For example, the corresponding nucleic acidmolecule may be contained within a vector that encodes the peptide. Asdesired, the vector may be configured to express the peptide. The vectorcan also be comprised in a host cell. In an embodiment, the host cellexpresses the peptide. The peptide may be expressed on the surface ofthe host cell. Appropriate display systems are available in the art orare provided herein. For example, the host cell can be a microbial cell,a bacterial cell, an E. coli cell, a eukaryotic cell, a yeast cell, or amammalian cell.

The method of the invention may further comprise capturing members ofthe plurality of peptides that form a complex with members of theplurality of antibodies prior to step c). In an embodiment, thecapturing comprises capturing the peptide-bound members of the pluralityof antibodies. The peptide-bound members of the plurality of antibodiesmay be captured to a substrate. Any useful substrate can be used. Forexample, the substrate can be a planar surface, e.g., a plate well, or aplurality of microbeads (also referred to as microparticles). Theplurality of microbeads may be configured to facilitate capture asdesired. For example, the microbeads may be magnetic or carry a label,including without limitation a fluorescent label. The bound members ofthe plurality of antibodies can be captured using a reagent that bindsan antibody constant region. For example, the reagent can be Protein A,Protein G, Protein L and/or an anti-immunoglobulin antibody or aptamer.As desired, the reagent is coupled to the substrate, thereby allowingcapture of peptide-bound antibodies to the substrate.

In some embodiments, the method of the invention further comprisesfiltering the plurality of antibodies prior to step b). The filteringmay comprise contacting the plurality of antibodies with at least onereagent configured to deplete antibodies that bind to assay componentsother than the plurality of peptides. In an embodiment, the at least onereagent comprises a host cell as described herein, e.g., a host cellthat is configured to display members of the plurality of peptides. Thestep allows removal of antibodies that bind to the host cell itselfinstead of members of the plurality of peptides.

In another embodiment, the method of the invention further comprisesfiltering the plurality of peptides prior to step b). The filtering ofthe plurality of peptides may comprise contacting the plurality ofpeptides with at least one reagent configured to deplete peptides thatform a complex with assay components other than the plurality ofantibodies. In an embodiment, the at least one reagent configured todeplete peptides comprises Protein A, Protein G, Protein L, and/or ananti-immunoglobulin antibody or aptamer.

As desired, filtering of both the plurality of antibodies and theplurality of peptides can be performed.

In some embodiments, the methods of the invention further comprisedetermining at least one peptide motif from the members of the pluralityof peptides identified in c). The determining may comprise aligning thesequences of the members of the plurality of peptides identified in c).The aligning may comprise using a computational alignment algorithm.Such algorithms are known in the art or provided herein. For example,the MEME program may be used as described further below.

The following paragraphs provide an exemplary protocol when performingthe methods of the invention using peptide libraries displayed on E.coli cells to identify antibody specificities in blood (serum) samples.One of skill will appreciate that these methods can use alternatedisplay configurations and/or alternate sample sources. Various usefulalternatives are described elsewhere herein. Certain steps would then bealtered or perhaps skipped accordingly.

1) Serum depletion step: Antibodies in the starting sample that bind toassay components are first removed to favor recovery of antibodies whichbind displayed peptides. For example, antibodies targeting E. coli cellscan be removed by incubating serum with an E. coli strain expressing thelibrary scaffold alone (i.e., no peptides). After the incubation, thebacteria along with any bound antibodies are removed usingcentrifugation and collection of the supernatant (unbound antibodies).

2) Library clearing step: The peptide display libraries can also becleared of peptides that may form a complex with particular assaycomponents. For example, peptide libraries can be cleared of protein Aand protein G binders by incubating the induced library with magneticbeads coated with protein A and protein G. Magnetic separation capturesthe beads along with any cells that are bound to the protein coating thebeads. The unbound fraction is collected for screening for serumantibody binders.

3) Antibody binding step: The serum and peptide display libraries arecontacted to allow antibodies present in the serum sample to bind topeptides displayed on the E. coli cells. For example, the depleted serumsample can be incubated with Protein A and G cleared cells expressingthe peptide library. Antibodies from serum bound to expressed peptideson the cells are harvested using centrifugation followed by washing toremove non-specific interactions.

4) Library enrichment step: The above step allowed formation ofcomplexes between the antibodies and displayed peptides. These complexesare now recovered. Washed cells are then incubated with magnetic beadscoated with protein A and protein G to capture antibodies from theserum, which will also capture the cells expressing peptides that arebound by antibodies. The beads are washed several times while magnetizedto remove cells captured non-specifically.

6) Growth step: The final enriched display library (i.e., cellsdisplaying peptides that remain bound to washed beads) is recovered. Thecells can be resuspended in growth broth (e.g., LB) and allowed toreplicate. Alternatively, one can proceed directly to step 9 or step10a.

7) Repeat enrichment step: The above steps can be repeated as desired.For example, a second round can further enrich for peptide members ofthe library that interact with antibodies from serum and reducenon-specific binding cells that may have come through the first round ofthe screen.

8) Enrichment analysis step: After the one or more rounds of enrichmentare completed, the final enriched library is analyzed to confirm andquantify binding of library members to patient serum antibodies (qualitycontrol for enrichment). Such analysis can use flow cytometrymethodology (FACS).

9) DNA isolation from enriched library step: Each cell contains DNAencoding the peptide that cell displays on its surface. An E. coli cellmay contain a plasmid vector encoding the peptide. The plasmid isisolated from the enriched library from each serum sample forpreparation for sequencing analysis.

NGS technology can be used sequence large numbers of plasmid in a singlereaction. Various platforms exist for NGS analysis. Below arealternative methods using the Illumina, Inc. or Life Technologies(Thermo Fisher) platforms. Unless otherwise specified herein, themethods of the invention may employ any appropriate NGS technology.

10a) Amplicon preparation step: (For sequencing using the Illuminaplatform—MySeq, NextSeq, HiSeq) The “region of interest” (random/peptideregion from the library) is amplified using the plasmid as template withforward and reverse primers that flank the random region. The primerscontain adaptors specific for use on the Illumina NextSeq. The PCRproduct is cleaned using magnetic beads that bind DNA and the resultingproduct is subjected to a second PCR using primers specific to theadaptors from the first PCR. The second PCR primers are provided by anIllumina (Nextra XT) indexing kit. The second PCR primers contain 8nucleotide indicies to provide a unique index combination specific tothe amplicon from each sample for tracking of the sample during thesequencing.

10b) Amplicon preparation step: (For sequencing using the Ion platform(Life Technologies)—Personal Genome Machine, Proton) The “region ofinterest” (random/peptide region from the library) is amplified usingthe plasmid as template with forward and reverse primers that flank therandom region. The primers contain adaptors specific for use on the IonProton along with a unique barcode for each sample that will be pooledfor sequencing. The PCR product is cleaned using magnetic beads thatbind DNA.

11) Amplicon quality control step: After cleaning the second PCRproduct, the purity is confirmed using gel electrophoresis or aBioanalyzer 2100 and the quantity of the DNA is determined. Ampliconsspecific for the enriched libraries from all serum samples screened arenormalized and pooled at equal molar concentrations for running on thesequencer.

12a) Sequencing step: The amplicon pool is run on the Illumina NGSinstrument per instructions from the manufacturer. Using the NextSeqinstrument, a 75 cycle high-output flow cell is used with single readand dual indexing settings. These specifications allow for approximately400 million total sequences, are sequenced once in the “forward”direction for a length of 75 base pairs (fully covering the 12 aminoacid random region in the library), and are also read for both 5 primeand 3 prime indices.

12b) The amplicon pool is run on the Ion Proton instrument perinstructions from the manufacturer (Life Technologies).

13) Sequence de-multiplexing step: If required, the resulting sequencesare de-multiplexed using the index codes to identify which serum samplesthe sequences originated from. Indexed sequences are sorted for eachsample and subjected to bioinformatics analysis. This analysis maycomprise identifying peptide sequences from their respective DNAsequences as determined above. Thus, the peptide signatures or epitoperepertoires of the sample/s are determined.

A peptide display library is enriched for library members that bindantibodies within a sample. The library of peptides can be displayed onany useful biological entity, e.g., microbial cells such as bacteria,phage, synthetic beads, yeast cells, or ribosomes. The library may havea high diversity of more than 10⁵ unique library members, e.g., morethan 10⁶, 10⁷, 10⁸, 10⁹, 10¹⁰, or more than 10¹¹ members. Variouspeptide library compositions can be used including fully random peptidelibraries of 3-30 random positions, or using libraries with one or morepositions fixed to cysteine to favor the formation of disulfide bonds.Disulfide bonds may increase the affinity of some antibody bindingpeptide epitopes. Additionally, libraries derived from structuralscaffolds can be used including for example, helix-turn-helix (i.e.,alpha-alpha), beta-hairpins, alpha-beta, beta-alpha, beta-sheets, zincfingers, or protein interaction modules including SH2, SH3, and otherdomains. In some embodiments, the length of random region is chosen tobe 10-20 amino acids, e.g., 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20amino acids. The random region can have more than 20 amino acids ifdesired. A peptide library may be configured to i) possess a minimumnumber of stop codons (that prevent peptide display), and ii) minimizesbias towards certain amino acids that are more abundant in librariesconstructed using NNS or NNK codons. One method to accomplish this isprepare synthetic oligonucleotides for PCR reactions, using 20triplet-phosphoramidites (DNA molecules composed of three bases) thatuniquely encode one of the 20 amino acids. Preparation of such librariesis a method known to those skilled in the art of peptide and proteinlibrary construction. See, e.g., Directed Evolution Library Creation:Methods and Protocols (Methods in Molecular Biology) Softcover reprintof hardcover 1st ed. 2003 Edition by Frances H. Arnold (Editor), GeorgeGeorgiou (Editor); ISBN-13: 978-1617374715.

In some embodiments of the invention, the sample to be analyzed is firstdepleted of antibodies that bind to the biological entity displaying thepeptide (e.g., phage, bacteria, yeast, ribosomes, cells), by incubatinga mixture of sample containing the antibodies with an excess of thebiological entity that does not display a peptide. The entities bound toantibodies are then separated using centrifugation, filtration,sedimentation, or other separation method, and the unbound antibodiesare recovered to generate a “depleted sample.” The depleted sample isthen mixed with, and allowed to contact the library to allow complexesto form between the antibodies and displayed peptides. The mixture canbe allowed to incubate for any desired time, e.g., 1, 2, 3, 4, 5, 6, 7,8, 9, 10 or more than 10 h. Antibodies that are not bound to librarypeptides are removed from the mixture, e.g., using centrifugation orsedimentation, and recovered antibody-peptide complexes are resuspendedinto a buffered salt solution. Library members with bound antibodies canbe captured using Protein A and/or Protein G to bind to the constantregions of the peptide-bound antibodies, or with anti-human Igantibodies. The Protein A, Protein G or anti-human antibodies can bebound to a substrate to facilitate capture. For example, the substratecan be a planar surface or bead. In an embodiment, the Protein A,Protein G or anti-human antibodies are coupled to magnetic beads.Labeled cells are then separated using magnetic separation or magneticactivated cell sorting (MACS), and recovered into growth media toamplify the population of selected cells. This process typically resultsan enrichment of antibody binders in the library from an initialfrequency of 0.5-5% to about 50-60% binders. To increase the fraction ofbinders in the population, and the quality of useable data, the sortingprocess above can be repeated one or more times to increase the purityof binders within the enriched library, typically to >85%.

Sample preparation for sequencing: As described herein, the amino acidsequence of the bound peptides can be determined by sequencing DNAencoding the peptides. In an embodiment, the peptides are encoded onplasmid DNA comprised in a host cell. The plasmid DNA can be isolatedfrom the cells and the sequence of the DNA encoding the peptides isdetermined. In some embodiments, the plasmids are used as a template forpolymerase chain reaction PCR to create an amplicon library. As desired,each amplicon library enriched against a distinct sample can be given aunique nucleic acid sequence identifier or “bar code” embedded withinthe amplicon library. This step allows many amplicon libraries to bepooled together and analyzed in a single NGS run.

Sequencing of the samples is then performed. In some embodiments, NGSsequencing is used. The raw DNA sequences are translated into amino acidsequences. If necessary peptide variants arising from sequencing errorsare identified as sequences exhibiting identity beyond what isstatistically probable. For example, for a 12-mer random peptide librarywith 12 random amino acid positions, sequences having 10 or 11identities are unlikely to be unique, since the library contains10{circumflex over ( )}10 members. The probability of finding twosequences with 10 identities in a library of this size constructed usingtriplet phorphoramidites is low.

In one embodiment of the invention, a listing of all unique peptides,along with the number of observations (counts) observed in each sampleanalyzed is generated. From this unique sequence listing, peptidesoccurring two or more samples obtained from individuals having a givenphenotype are enumerated and motifs occurring in those peptides areidentified using one or more established motif discovery algorithms,e.g., sequence clustering algorithms such as MEME, available atwww.meme-suite.org [13-15]. This step identifies the commonalitiesbetween antibody specificities directed towards the same antigens fromdifferent individuals. One benefit of finding commonalities in aplurality of samples is that this may more accurately identify aspecific motif that can be used to search the epitope repertoires frommany different samples. And, the motif will more closely match thecorresponding epitope sequence of the antigen that gave rise to theantibody.

The above approach has been applied to serum samples from healthy donorsto identify hundreds of motifs. See the Examples herein for details.

For sequence clustering algorithms whose computation time scales as˜N{circumflex over ( )}2, the number of sequences accessed can bereduced to facilitate efficient computations. For example, with currentcomputing power, a size of about 5000 sequences may restrain computationtime to a period of less than 12 hrs. However, greater computer powerand efficiency and longer computer time can increase the number ofsequences used for clustering along with quality and number of motifsgenerated.

Increasing the number of motifs by computational depletion. In order toidentify a larger number of distinct antibody specificities within theepitope repertoire, peptides containing motifs constructed from thelargest number of representative sequences (e.g. the motifs with thelargest number of “sites” from MEME) are removed from a set of peptidesmost specific to a sample or set of samples. The set of peptides shouldbe large enough that after performing computational depletion the fileis approximately the same size as the file used for the first round ofclustering. See, e.g., [13-15]. The resulting depleted file is then usedfor a new run of sequence clustering for motif discovery. The processcan be iterated as desired to identify motifs corresponding to lessabundant antibodies within the repertoire whose presence may beimportant for diagnosis. Computational depletion can identify newmotifs, and improve the quality of motifs identified without depletion.

To identify common motifs within the NGS dataset of a single sample, theset of peptides that are present in the sample and also present in oneor more other samples selected from a group of samples is determined.This reduced set of peptides can be analyzed using peptide sequenceclustering algorithms.

Method to Discover Disease-Specific Epitopes and Motifs

In another embodiment of the invention a listing containing all uniquepeptides, along with the number of observations (counts) observed ineach sample analyzed is generated. The listing is contained in acomputer file. From this file, peptides that exhibit the highestspecificity and sensitivity for the disease can be identified as thoseoccurring in the largest number of samples from individuals withdisease, but the smallest number of samples from individuals withoutdisease. For example, if epitope repertoires are determined for 20samples from individuals with disease and 20 from age and gender matchedcontrols, then peptides present in more than 10 of 20 disease samplesand in none of 20 controls samples (or e.g., <2/20 controls) can be usedas input for motif discovery via clustering (e.g., MEME). All peptidespresent in 1-20 disease samples (e.g., 20/20,19/20, 18/20/17/20,16/20,15/20, 14/20, 13/20, . . . 1/20 etc.) can analyzed by sequenceclustering algorithms (e.g., MEME). For peptides present in exactly Nsamples out of a total of M samples, a threshold number of N can bedetermined such that the number of peptides within N/M samples can beanalyzed using peptide sequence clustering algorithms.

Alternatively, individual peptides that occur in the largest number ofdisease samples and the fewest (or none) control samples can be aligned.In some embodiments, to identify diagnostic compositions, individualpeptides exhibiting the highest disease sample specificity (present inthe largest number of disease samples, and fewest control samples) areassayed for reactivity with new samples from individual samples with andwithout disease to validate their diagnostic utility, and estimate theirdiagnostic sensitivity and specificity.

To identify those motifs with the most utility for diagnostic use, theenrichment of individual motifs can be calculated in an arbitrary numberof samples from healthy controls or other disease controls to identifymotifs with the highest specificity. For example, if a motif appears infewer than 5% of many samples from individuals without CD, or untestedcontrols, but more than 10% of CD cases the significance of enrichmentcan be calculated using statistical methods to determine a p-value.

Calculating Enrichment

As described herein, the compositions and methods of the invention canbe used for determining or measuring an antibody specificity in a sampleby determining enrichment of antibodies against various peptide orpeptide motifs of interest. An exemplary flow diagram is shown in FIG.2A. Peptide signatures and/or motif(s) specific to a phenotype ofinterest are determined as described herein 201. See, e.g., FIG. 1 andrelated discussion above. A sample comprising antibodies (Ig) iscollected from a subject 202. The sample is contacted with a peptidelibrary as described herein and the library is screened for peptidebinders to the antibodies in the sample 203. Peptide sequences that arebound by antibodies in the sample are determined as described herein,e.g., using NGS 204. The enrichment of given peptides is calculatedamongst the determined peptide sequences 205. This step may alsocomprise determining peptide motif(s) present in the sample as describedherein. The calculated enrichment(s) of the peptides and/or motifs ofinterest may be used for further analysis as desired, e.g., to compareto established thresholds in order to characterize the sample 216.

In order to detect a given antibody directed towards a predefined aminoacid sequence, pattern, or motif, the number of sequence, patterns, ormotifs occurring within a sample NGS dataset can be counted, motifenrichment can measured as the number of observations of thatsequence/pattern/or motif divided by the number of instances expected byrandom chance. For example, if one million unique 12-mer peptidesequences from a library constructed using 20 triplet phosphoramidates(i.e., one codon per amino acid) were obtained for a sample, and thedistribution of amino acids within the sample was assumed to beapproximately random one would expect the pattern QPXXPF (SEQ ID NO: 5)to occur about [(1/20)⁴ instances/frame×(7 frames)×10⁶=43.74 by randomchance.

If the number of instances of this motif/pattern is larger than thisnumber, e.g., 272, one can calculate the enrichment as272/43.75=6.2-fold and the significance value for the level ofenrichment observed can be calculated using an appropriate statisticaltest (e.g. t-test, z-test, U-test, rank-sum test, etc).

Characterization of Phenotypes

As described herein, the compositions and methods of the invention canbe used for characterizing a phenotype of interest, e.g., to provide adiagnosis, prognosis, or theranosis of a condition such as an infectionor autoimmune disorder. An exemplary flow diagram is shown in FIG. 2B,FIG. 3. Peptide signatures and/or motif(s) specific to a phenotype ofinterest are determined as described herein 211. See, e.g., FIG. 1 andrelated discussion herein. To characterize phenotype in a subject, e.g.,a human subject having or suspected of having a medical condition, asample comprising antibodies (Ig) is collected from the subject 212. Thesample is contacted with a peptide library as described herein and thelibrary is screened for binder to the antibodies in the sample 213.Peptide sequences that are bound by antibodies in the sample aredetermined as described herein, e.g., using NGS 214. The enrichment ofgiven peptides is calculated amongst the determined peptide sequences215. This step may also comprise determining peptide motif(s) present inthe sample as described herein. The calculated enrichment(s) of thepeptides and/or motifs of interest is compared to established thresholds216. This comparison is used to characterize the phenotype, e.g., toprovide a positive, negative or equivocal diagnosis of a condition.

The thresholds may be referred to herein as cut-offs, control values,reference values, or the like. One of skill will understand that themanner in which a threshold is calculated can depend on the phenotypeand desired characteristics. For example, to determine an exposure togiven entity, e.g., a pathogen, the threshold may be the expected randomoccurrence of the enrichment value (i.e., 1) or close to zeroobservations. In this setting, an enrichment greater than the thresholdcan indicate exposure to the entity. In other settings, the thresholdmay be the enrichment observed in one or more control sample. Forexample, if the phenotype to be characterized is a disease or disorder,the threshold may be the enrichment observed in a sample without thedisease or disorder. In this setting, an enrichment greater than thethreshold can indicate the presence of the disease or disorder. In somecase, the degree of enrichment may provide further information,including without limitation the severity, stage, grade, or progressionof the disease or disorder. One of skill will appreciate how to selectan appropriate control given the desired phenotype to be characterized.One of skill will also appreciate that enrichment above or below thethreshold may be relevant given a particular setting. A threshold valuecan be chosen to provide the desired balance between sensitivity andspecificity, or according to other relevant statistical measures.

The following paragraphs provide an exemplary protocol when performingthe methods of the invention using peptide libraries displayed on thesurface of a display host. One of skill will appreciate that thesemethods can use alternate display configurations and/or alternate samplesources. Various useful alternatives are described elsewhere herein.

In an embodiment, a body fluid sample from an individual is collected.Antibodies that bind to the display library scaffold (bacteria, virus,phage, etc) are first depleted from the sample by contacting thespecimen with the display host that does not express a member of thepeptide library. Antibodies that do not bind to the host are recovered.In some embodiments of the invention, E. coli display technology isused. In such cases, the display scaffold eCPX [18] can be expressed onthe cell surface without an appended peptide sequence. An aliquot ofcells is washed once, and resuspended in a pH buffered salt solution.The body fluid sample after these steps may be referred to herein as a“depleted sample.”

The depleted sample is then incubated with the peptide display libraryunder conditions that allow binding of antibodies in the sample withdisplayed peptides. Peptide library members that are bound to antibodiesin the sample are separated. In some embodiments, separation is achievedusing by capturing the antibody-peptide complexes to a substrate. Thesubstrate can be coupled to one or more binding agent to the constantregion of the antibodies in the sample, thereby facilitating capture. Insome embodiments, the substrate comprises microparticles (beads) thatare functionalized with a binding agent to antibodies, e.g., Protein A,Protein G, Protein L, or an Ig binding antibody. The microparticles maybe magnetized to allow for capture using magnetic force. The process maybe repeated as desired, e.g., to increase the purity of antibody bindinglibrary members.

From the enriched library, an amplicon library of the DNA encoding themembers of the peptide library may be prepared for DNA sequencing. Thedetermined DNA sequences are translated into peptide sequences accordingto typical genetic code, thereby providing a peptide signature for thesample. The number of instances of each unique peptide in the sample maythen be counted. Enrichment of peptides and motifs can be calculated asdesired. For example, the number of instances of each peptide, pattern,or motif is tabulated, and divided by the number predicted to occur byrandom chance according to established probability methods.

In some embodiments, the method is used to provide a diagnosis. Apredetermined disease-specific peptide, pattern, or motif indicative ofthe disease can be determined using the methods herein. To diagnose asubject, the peptide signature for the sample from the subject iscompared to a predetermined peptide signature of interest. If theenrichment of the appropriate peptide, pattern, or motif is increasedbeyond an established threshold, then the individual can be diagnosedwith disease. An enrichment threshold can be appropriately determined bydetermination of the enrichments and their standard deviation within aset of samples from individuals that do not have disease and a separateset with disease (i.e. a reference set). A threshold value can be chosento provide the desired balance between sensitivity and specificity.

The Examples herein provide a number of examples wherein the methods ofthe invention were used to determine peptide signatures for variousdisease settings. For instance, Example 1 provides an application of themethods of the invention to Celiac disease (CD). As further described inthe Example, a disease specific motif was identified from a set of 16 CDsamples and 13 healthy controls. For the motif QPXXPFX[ED] (SEQ ID NO:4), a threshold enrichment value that maximizes specificity (100%) andsensitivity (95%) is enrichment>11. Accordingly, if a motif is observedin a test sample with an Enrichment value of 11 or more, the individualmay be diagnosed with CD. Diagnostic sensitivity and specificity may befurther improved by combining multiple motifs. A set or panel of fourmotifs (QXXXPF[PS]E (SEQ ID NO: 6), PFSEM (SEQ ID NO: 7), PFSEX[FW] (SEQID NO: 8), QPXXPFX[ED] (SEQ ID NO: 4) correctly identifies all diseaseand control samples in both discovery and validation datasets FIG. 5.

The accuracy of detection of an antibody specificity can be improved beincreased by combining the enrichment values of two or more sequences,patterns, or motifs in a linear, non-linear, or weighted average.

Combining Diagnostic Assays into One Test

In an aspect, the present invention enables combination or aggregationof multiple assays into one multiplexed assay. The invention may achievesuch multiplex analysis without additional labor or cost. Combiningassays can be accomplished by performing searches of the peptidesignature with two or more disease specific motif sets. For example, onecan use the Celiac Disease specific peptides or motifs selected fromQXXXPF[PS]E (SEQ ID NO: 6), PFSEM (SEQ ID NO: 7), PFSEX[FW] (SEQ ID NO:8), QPXXPFX[ED] (SEQ ID NO: 4) alone or in combination with an arbitrarynumber of motifs or motif panels associated with other diseases. As afurther example, the invention can be used to simultaneously assess asample for infection with Borrelia burgdorferi, Babesia sp., Anaplasmasp., Erlichia sp, Toxoplasma gondii, Toxocara canis, Taenia solium,Trypansoma cruzi, HIV, Epstein-Barr virus infection, Zika virusinfection and any other condition associated with an antibody response.In such cases, the enrichment of each the disease specific motifs foreach disease can be calculated in same manner as for a single disease.An arbitrary number of enrichment calculations can be performed with agiven sample. All enrichments that exceed diagnostic thresholds can thenbe used to make a diagnosis. Accordingly, the compositions and methodsof the invention can be used to screen individuals for the presence ofvarious conditions, such as autoimmune diseases and/or infectiousagents, in a single assay.

Identification of Peptides, Patterns, and Motifs that Correspond toKnown Individual Biomarkers

The diagnosis of many individual autoimmune diseases is aided byseparate individual tests or panels that detect the presence of commonautoantibodies. For example, there are individual tests available foranti-nuclear antibody (ANA), Rheumatoid factor, anti-double stranded DNAantibody (anti-dsDNA), anti-citrulinated peptide (CP), anti-actinantibody, anti-neutrophil cytoplasmic antibody (ANCA) and others. Thepresent invention provides a means to identify peptides, patterns, andmotifs that indicate whether one or more of these common autoantibodiesis present.

Briefly, one or more samples is analyzed by display-seq as describedherein, with and without physical depletion of the target antibodyspecies. For example, to identify motifs that correspond to the knownantigen SS-A/Ro, or SS-B/La, a sample demonstrated to containing theseantibodies is incubated with cells that display peptides containingputative known antigen motifs (e.g., motif presence is equivalent withSS-A positivity), to affect depletion of antibodies that bind to theknown antigen. The original and the depleted samples can be assayed forthe presence of antibodies that bind to the known target antigen. Cellsdisplaying motifs that remove, attenuate, or reduce the antigen specificsignal (e.g., Absorbance, light emitted, radioactivity, etc) indicatethe motif that corresponds to the known antigen.

Identification of Peptides, Patterns, and Motifs that Indicate thePresence of an Autoimmune Disease

Autoantibodies have been implicated in a variety of autoimmune diseasesand disorders. The type of autoimmune condition and amount of injury tothe host organism depend upon the systems and organs targeted by theautoantibodies. In some cases, autoimmune disorders are caused byautoantibodies that primarily affect a single organ and are relativelyeasier to diagnose and the signs and systems of disease are related tothat organ. Examples include targeting of the thyroid in Graves diseaseor Hashimoto thyroditis. However, other diseases and disorder may becaused by systemic autoantibodies that effect multiple systems andorgans, making such conditions much harder to diagnose. Patients maypresent with non-specific symptoms such as joint pain, fatigue, fever,rash, cold symptoms, weight loss and muscular weakness. In addition,certain diseases, including Crohn's disease, Lupus, Sjogren's syndrome,and mixed connective tissue disease, are diagnosed using biomarkers thatindicate a disease is present but do not identify which disease ispresent. Examples of such non-specific antibody biomarkers includenuclear antibody (ANA), rheumatoid factor, anti-actin antibody,anti-neutrophil cytoplasmic antibody (ANCA), anti-SS-A, and anti-SS-B.Even though diagnostics to detect these biomarkers may not identifyspecific disease, they are a useful aid to clinicians, suggesting thatfurther testing and diagnostic work-up should be performed. Even so,some of these tests are cumbersome to perform, and lack quantitativeprecision, or require a pathologist to determine the staining patternfor example for ANA or ANCA tests.

The present invention provides a means to identify peptides motifs andpatterns that indicate an autoimmune disease is present, providingquantitative objective rationale for further testing. The inventiontherefore provides meaningful benefits over the other above mentionedtesting because the invention allows multiple tests to be performedquickly, automatically, and quantitatively for a given sample using thedisease specific motifs.

Peptide Signatures and Motifs

The present invention provides compositions and methods to determinesignatures of antigenic peptides in a sample comprising a plurality ofantibodies. The methods of the invention further comprise determiningpeptide motifs from a peptide signature. Such peptide signatures andmotifs can be used to characterize a phenotype in a sample, such asdetecting the presence of a medical condition in order to provide adiagnosis. In some cases, the motifs determined by the subject methodsmay be correlated with various antigens involved in the disease process.For example, a motif determined by the subject methods may be correlatedwith a peptide from an allergenic protein or a self-antigen in case ofautoimmune conditions.

In an aspect, the invention provides peptides and peptide motifs thatare indicative of various conditions. Such peptides motifs are disclosedherein. For example, motifs indicative of various conditions aredisclosed in the Examples.

In some embodiments, motifs that are indicative of mononucleosis byEpstein Barr Virus (EBV) infection are any one or more of LFGxx[LM]N(SEQID NO: 9); GETxGQ,(SEQ ID NO: 852); EWVxx[YF]D(SEQ ID NO: 10),P[LM]ALxL(SEQ ID NO: 11), KxNExWxV (SEQ ID NO: 12), P[AG]xRTxK(SEQ IDNO: 13), AYTxVN(SEQ ID NO: 14), WN[AS]YxxxN(SEQ ID NO: 15),[RKE]xxWxP[LM]Q(SEQ ID NO: 16), [AS]YxSx[SA][YF](SEQ ID NO: 17), ExYxSPS(SEQ ID NO: 18), MNIxDD (SEQ ID NO: 19), EH[ANK]FW (SEQ ID NO: 20),VHNAY (SEQ ID NO: 21), HG[EA]xLN(SEQ ID NO: 22), [GD]xx[LF]xxP[ML]Q (SEQID NO: 23), [LVMI]xNAx[TS][FGI](SEQ ID NO: 24), PxNSYT (SEQ ID NO: 25),RxxPLAxxL (SEQ ID NO: 26), CPKxNxT (SEQ ID NO: 27), Q[PA]H[AM]F (SEQ IDNO: 28), PAxENxxx[GSP] (SEQ ID NO: 29), NID[DE]D (SEQ ID NO: 30),RxQx[VS]D[NA] (SEQ ID NO: 31), Wx[DP]PxHL (SEQ ID NO: 32), TWA[FI][FI](SEQ ID NO: 33), EDxGHP (SEQ ID NO: 34), [ETA]xxx[YF]xxP[SR]Q (SEQ IDNO: 35), GMxP[RK]Q (SEQ ID NO: 36), Wxx[VI]RxxPxQ (SEQ ID NO: 37),[NE][AG]Y[SAT]xxW (SEQ ID NO: 38), KxI[ST]xYW (SEQ ID NO: 39), YYxYRxxK(SEQ ID NO: 40), KxHExG[FY] (SEQ ID NO: 41), [MLF]xNPQQ (SEQ ID NO:853); HHFL[VI] (SEQ ID NO: 42), [LV]CNAY (SEQ ID NO: 43) or combinationsthereof.

In some embodiments, peptides indicative of mononucleosis by EBVinfection are any one or more of LFGanLN (SEQ ID NO: 44), PGpRTcK (SEQID NO: 45), PArRTrK (SEQ ID NO: 46), IaNAgSI (SEQ ID NO: 47), WaqIRhiPyQ(SEQ ID NO: 48) or MrNPQQ (SEQ ID NO: 49) or combinations thereof.

In some embodiments, motifs that are indicative of Rhinovirus infectionare any one or more of L[EDQ]EV[LIV][IV][DE]K (SEQ ID NO: 50),E[VI][VIL][IV][DEN]K (SEQ ID NO: 51), E[VI][VI][VI]XK (SEQ ID NO: 52),VXPNI (SEQ ID NO: 53), VVPN (SEQ ID NO: 54), LXEVLVVVP (SEQ ID NO: 55),GPXHTXKV (SEQ ID NO: 56), EXY[VI]DX[VT]LN (SEQ ID NO: 57) orcombinations thereof.

In some embodiments, peptides indicative of Rhinovirus infection are anyone or more of FLEFV[IV]VDK (SEQ ID NO: 58), LNEVLVVVPNI (SEQ ID NO:59), GPKHTQKV (SEQ ID NO: 60), EEYVDQVLN (SEQ ID NO: 61) or combinationsthereof.

In some embodiments, motifs that are indicative of Cytomegalovirusinfection are any one or more of KXDPDXXW[ST] (SEQ ID NO: 62) or KPXLGGK(SEQ ID NO: 63) or combinations thereof.

In some embodiments, peptides indicative of Cytomegalovirus infectioninclude the set of peptides specified by K[YH]DPDE[SFL]WT (SEQ ID NO:64); (i.e. some positions vary between different strains of CMV), andKPtLGGK (SEQ ID NO: 65) or combinations thereof.

In some embodiments, motifs that are indicative of Streptococcusinfection are any one or more of [IV]X[PR]QPEKP (SEQ ID NO: 66), KXDDMLN(SEQ ID NO: 67), KXDXMLN (SEQ ID NO: 68), LW]XSAEXEEK (SEQ ID NO: 69),SAEXEXK (SEQ ID NO: 70) or combinations thereof.

In some embodiments, peptides that are indicative of Streptococcusinfection are any one or more of VKPQPEKP (SEQ ID NO: 71), KTDDMLN (SEQID NO: 72), LESAEKFFK (SEQ ID NO: 73) or combinations thereof.

In some embodiments, motifs that are indicative of Toxoplasma gondiiinfection are any one or more of HExE[FY]Q (SEQ ID NO: 74), LD[MLF]WxE(SEQ ID NO: 75), HCSAC (SEQ ID NO: 76), [FY]xGVVN (SEQ ID NO: 77),KxxxGRGxI (SEQ ID NO: 78), GPH[LA]E (SEQ ID NO: 79), PRREP (SEQ ID NO:80), CNxxxECY (SEQ ID NO: 81), KxCQPxxC (SEQ ID NO: 82), PxPD[FH][TS](SEQ ID NO: 83), NxxxExY[AG]xD (SEQ ID NO: 84), P[AG]AxxLD (SEQ ID NO:85), MPSxSxE (SEQ ID NO: 86), [RK]xYxHR[TS] (SEQ ID NO: 87), K[PA]xFxFxK(SEQ ID NO: 88), DD[CST]xGxR (SEQ ID NO: 89), P[ML]xxHxMY (SEQ ID NO:90), Kx[ASQ][SAT]xRG (SEQ ID NO: 91), [DG]QPEN (SEQ ID NO: 92),[KHR]N[QN]DG (SEQ ID NO: 93), Nx[EVS]GExY (SEQ ID NO: 94), FP[VI]TG (SEQID NO: 95), HGM[PA][KR] (SEQ ID NO: 96), [VIT]PWIF (SEQ ID NO: 97),Kx[STN]VxFQ (SEQ ID NO: 98), [VAI]WSGS (SEQ ID NO: 99), FS[LIAM]xxWG(SEQ ID NO: 100), PTN[PQ]G (SEQ ID NO: 101), [RK]Kxx[YW]xHx[TS] (SEQ IDNO: 102), [HRW]xxHPRF (SEQ ID NO: 103) or combinations thereof.

In some embodiments, motifs that are indicative of Trypansoma cruziinfection (Chagas disease) are any one or more of [RK]MRxID (SEQ ID NO:104), QHxGHP (SEQ ID NO: 105), KxxLPED (SEQ ID NO: 106), [IV]LxxFGY (SEQID NO: 107), PLDxxxxIS (SEQ ID NO: 108), ETXIPXE (SEQ ID NO: 109),[VI]Nx[DE][ML]YxP (SEQ ID NO: 110), FLxxIGA (SEQ ID NO: 111),D[VI]x[MI][ILV]x[KR] (SEQ ID NO: 112), RxSPYx[IL]F (SEQ ID NO: 113),VGPRH (SEQ ID NO: 114), PQxQH[ED] (SEQ ID NO: 115), PxxGGFG (SEQ ID NO:116), KxEGxxMG (SEQ ID NO: 117), KxxGxTxxLS (SEQ ID NO: 118), EMG[FW]Q(SEQ ID NO: 119), [VI]KxGxxDxP (SEQ ID NO: 120), PE[DN]ExYP (SEQ ID NO:121), HYEWA (SEQ ID NO: 122), [HR]SNMxF (SEQ ID NO: 123), M[TV]GxxYE(SEQ ID NO: 124), DXX[KH]EXXLL (SEQ ID NO: 125), RxxWx[EDA]x[IV][AR](SEQ ID NO: 126), PxthocAx[GPA][TS] (SEQ ID NO: 127), PDxxSxT[ARG] (SEQID NO: 128), GRExDG (SEQ ID NO: 129), GVPGxxxK (SEQ ID NO: 130),[LM]xxx[EDQ]VxxIM (SEQ ID NO: 131), SxxxVSGG (SEQ ID NO: 132),A[KR]AG[DN]K (SEQ ID NO: 133), F[RN]xIN[RQ] (SEQ ID NO: 134), YXPVXPXSY(SEQ ID NO: 135), KxTFPD (SEQ ID NO: 136), PFM[FVM]xxR (SEQ ID NO: 137),EFWEP (SEQ ID NO: 138), [FY]GALS (SEQ ID NO: 139), PxGTEN (SEQ ID NO:140), Gx[KE]PWE (SEQ ID NO: 141), D[IV]Tx[YF][WN] (SEQ ID NO: 142) orcombinations thereof.

In some embodiments, peptides are indicative of Trypansoma cruziinfection (Chagas disease) are any one or more of QHkGHP (SEQ ID NO:143), QHiGHP (SEQ ID NO: 144), KalLPED (SEQ ID NO: 145), KkhLPED (SEQ IDNO: 146), KitLPED (SEQ ID NO: 147), KtiLPED (SEQ ID NO: 148), KvlLPED(SEQ ID NO: 149), VLkkFGY (SEQ ID NO: 150), LhlFGY (SEQ ID NO: 151),VLgeFGY (SEQ ID NO: 152), VLepFGY (SEQ ID NO: 153), PLDvekeIS (SEQ IDNO: 154), PLDllkyIS (SEQ ID NO: 155), ETkIPsE (SEQ ID NO: 156), ETeIPsE(SEQ ID NO: 157), ETgIPfE (SEQ ID NO: 158), VNvDLYiP (SEQ ID NO: 159),FLgaIGA (SEQ ID NO: 160), FLlIIGA (SEQ ID NO: 161), FLkaIGA (SEQ ID NO:162), DIkMIeR (SEQ ID NO: 163), DifiVsR (SEQ ID NO: 164), DVhMLvR (SEQID NO: 165), DVdILeR(SEQ ID NO: 166), RvSPYsIF (SEQ ID NO: 167), VGPRH(SEQ ID NO: 168), PQkQHE (SEQ ID NO: 169), PQgQHD (SEQ ID NO: 170),KsEGefMG (SEQ ID NO: 171), KdEGlaMG (SEQ ID NO: 172), KdnGsTwsLS (SEQ IDNO: 173), KddGsTwaLS (SEQ ID NO: 174), IKqGrlDrP (SEQ ID NO: 175), HYEWA(SEQ ID NO: 176), MVGehYE (SEQ ID NO: 177), MVGkaYE (SEQ ID NO: 178),DqlKEgrLL (SEQ ID NO: 179), DvvKElmLL (SEQ ID NO: 180), DleKEneLL (SEQID NO: 181), DldKEvsLL (SEQ ID NO: 182), RhqWyAvVA (SEQ ID NO: 183),RhsWfDdVR (SEQ ID NO: 184), RkeWyDvVA (SEQ ID NO: 185), RdrWtEsIA (SEQID NO: 186), RatWlDqVR (SEQ ID NO: 187), RyvWnEwVA (SEQ ID NO: 188),PvDstAhGT (SEQ ID NO: 189), PlDcpAlGS (SEQ ID NO: 190), PaDssAhGT (SEQID NO: 191), PkDvkAtGS (SEQ ID NO: 192), pDvsAsGT (SEQ ID NO: 193),PgDlpAkAT (SEQ ID NO: 194), PaDvsAqAT (SEQ ID NO: 195), PpDvpAsGT (SEQID NO: 196), PDpaSiTA (SEQ ID NO: 197), PDasSsTA (SEQ ID NO: 198),PDsrSiTA (SEQ ID NO: 199), PDsrSvTA (SEQ ID NO: 200), PDskSpTA (SEQ IDNO: 201), PDseSpTA (SEQ ID NO: 202), GREsDG (SEQ ID NO: 203), GREaDG(SEQ ID NO: 204), GVPGshaK (SEQ ID NO: 205), GVPGcviK (SEQ ID NO: 206),LsprEVytIM (SEQ ID NO: 207), LtntDVtrIM (SEQ ID NO: 208), LedeDVlqIM(SEQ ID NO: 209), MadpEVaaIM (SEQ ID NO: 210), SqadVSGG (SEQ ID NO:211), SvgsVSGG (SEQ ID NO: 212), SpsgVSGG (SEQ ID NO: 213), SwfdVSGG(SEQ ID NO: 214), FRiINQ (SEQ ID NO: 215), FRaINR (SEQ ID NO: 216),KqTFPD (SEQ ID NO: 217), KaTFPD (SEQ ID NO: 218), PFMVqmR (SEQ ID NO:219), FGALS (SEQ ID NO: 220), YGALS (SEQ ID NO: 221), PsGTEN (SEQ ID NO:222), GfKPWE (SEQ ID NO: 223), DITdYN (SEQ ID NO: 224), DVTgFN (SEQ IDNO: 225) or combinations thereof.

In some embodiments, motifs that are indicative of Taenia solium(Cysticercosis) infection are any one or more of AxSPN[QEA] (SEQ ID NO:226), [RP]xAxSxNx[IFMLV] (SEQ ID NO: 227), PDxGVxP(SEQ ID NO: 869);NxxLGL[VT] (SEQ ID NO: 228), [YF]x[DE]IxxFF (SEQ ID NO: 229), IxHFFxG(SEQ ID NO: 230), [ILM][ILM][RK]H[ED]XQ (SEQ ID NO: 231), [ILM][RK]HExQ(SEQ ID NO: 232), KPxx[IL]xLx[KR] (SEQ ID NO: 233), NxDxxYYxx[WF] (SEQID NO: 234), GLDGP (SEQ ID NO: 235), RSxHthocN (SEQ ID NO: 236),FDxFN[IL] (SEQ ID NO: 237), TIFxGK (SEQ ID NO: 238), R[AV]xS[TQ]H (SEQID NO: 239), KWHGxY (SEQ ID NO: 240), MPEDK (SEQ ID NO: 241),Exxx[FY]x[AS]D[NT] (SEQ ID NO: 242), NQSxxKx[VI] (SEQ ID NO: 243),KxY[NAS]PY (SEQ ID NO: 244), [PQ][VL]HPRI (SEQ ID NO: 245), EDGMxxW (SEQID NO: 246), YASXQE (SEQ ID NO: 247), KQxQ[QK]E (SEQ ID NO: 248),K[AS]VFD[IVM] (SEQ ID NO: 249), PN[QE]x[DN]P (SEQ ID NO: 250),P[QA]XM[DN]I (SEQ ID NO: 251), [WR]x[RKH][ST]xFD (SEQ ID NO: 252),KxEPGxK (SEQ ID NO: 253), DDCLP (SEQ ID NO: 254), NXXXXGXHLE (SEQ ID NO:255), DXXHLEG (SEQ ID NO: 256), RPxx[TS]HN (SEQ ID NO: 257), KxHS[IV]Y(SEQ ID NO: 258), KxHSx[IV]S (SEQ ID NO: 259), MSGYE (SEQ ID NO: 260),YXIWGP (SEQ ID NO: 261), RxxWxMN[RK] (SEQ ID NO: 262), QPxxT[FY]E (SEQID NO: 263), YGYNQ (SEQ ID NO: 264) or combinations thereof.

In some embodiments, peptides that are indicative of Taenia solium(Cysticercosis) infection are any one or more of ArSPN (SEQ ID NO: 265),AgSpNr (SEQ ID NO: 266), PDgGVmP (SEQ ID NO: 267), NpkLGLT (SEQ ID NO:268) or combinations thereof.

In some embodiments, motifs that are indicative of latent Epstein-Barrvirus (EBV) are any one or more of GRRPFF (SEQ ID NO: 269), GGGxGAGGG(SEQ ID NO: 270), EG[PA]ST[GA]R (SEQ ID NO: 271), KXXSC[IVL]GC[RK] (SEQID NO: 272), SCIGCK (SEQ ID NO: 273), CIGC (SEQ ID NO: 274), VXLPHW (SEQID NO: 275), LPHW (SEQ ID NO: 276), PQDT[GA]PR (SEQ ID NO: 277), GPPWWP(SEQ ID NO: 278), QQPTTXGW (SEQ ID NO: 279), [LMIV]FDXDWYP (SEQ ID NO:280) or combinations thereof.

In some embodiments, peptides that are indicative of latent Epstein-Barrvirus (EBV) are any one or more of GRRPFF (SEQ ID NO: 281), GGGAGAGGG(SEQ ID NO: 282), EGPSTGPR (SEQ ID NO: 283), KRPSCIGCK (SEQ ID NO: 284),KEVKLPHWTPT (SEQ ID NO: 285), PQDTAPR (SEQ ID NO: 286), GPPWWP (SEQ IDNO: 287), QQPTTEGH (SEQ ID NO: 288), LFPDDWYP (SEQ ID NO: 289) orcombinations thereof.

In some embodiments, motifs that are indicative of HIV infection are anyone or more of CxGxLIC(SEQ ID NO: 290), CxxKx[IV]C[IV] (SEQ ID NO: 291),W[GAS]CxGxxxC (SEQ ID NO: 292), [RK]KL[IV]E (SEQ ID NO: 293), KLIMT (SEQID NO: 294), [QE]xxPFRY (SEQ ID NO: 295), CxxKx[IV]C[IV] (SEQ ID NO:296), [LF]xx[LIV][ND]KW (SEQ ID NO: 297), [AP][GC]GFG (SEQ ID NO: 298),LIx[TS]TY (SEQ ID NO: 299), [RK]KLxx[MV]Y (SEQ ID NO: 300),GF[GA][AQ][AYV] (SEQ ID NO: 301), GFG[RQ]x[FNY] (SEQ ID NO: 302),[KR]KxIH[VIM] (SEQ ID NO: 303), R[IV]PFG (SEQ ID NO: 304), KLIxx[TY]T(SEQ ID NO: 305) or combinations thereof.

In some embodiments, peptides that are indicative of HIV infection areany one or more of CSGKLIC (SEQ ID NO: 306), CSGKLICT (SEQ ID NO: 307),WGCSGKLIC (SEQ ID NO: 308), CSGKLICT (SEQ ID NO: 309), LLALDKW (SEQ IDNO: 310), AVGMG (SEQ ID NO: 311), LICTT (SEQ ID NO: 312), GFGAV (SEQ IDNO: 313), RKg,IrI (SEQ ID NO: 314), KKgIaI (SEQ ID NO: 315), RKgIhM (SEQID NO: 316), RKsIhM (SEQ ID NO: 317), KLICTT (SEQ ID NO: 318) orcombinations thereof.

In some embodiments, IgG motifs that are indicative of a Zika virusinfection are any one or more of VRxxYxQH (SEQ ID NO: 319), CEThoocHxC(SEQ ID NO: 320), DAEQxxR (SEQ ID NO: 321), WPGIF (SEQ ID NO: 322),CCYDXE (SEQ ID NO: 323), LxPDNxT (SEQ ID NO: 324), FxWGQxY (SEQ ID NO:325), KxEGElxvocA (SEQ ID NO: 326), CxxGxCQxK (SEQ ID NO: 327),CCxDxx[DE][ED] (SEQ ID NO: 328), RNGxED (SEQ ID NO: 329), [DE]xRxIYxQ(SEQ ID NO: 330), WxRCGL (SEQ ID NO: 331), D[ED]xRxxYxxH (SEQ ID NO:332), WCxLx[AV]N (SEQ ID NO: 333), LXTPWI (SEQ ID NO: 334), CWxxxGL[CA](SEQ ID NO: 335), ID[AV]EP (SEQ ID NO: 336), HF[NK][VT]xK (SEQ ID NO:337), QxNHQxK (SEQ ID NO: 338) or combinations thereof.

In some embodiments, IgM motifs that are indicative of a Zika virusinfection are any one or more of FExKEP (SEQ ID NO: 339), [FYW]DA[VI](SEQ ID NO: 340), DFDKR (SEQ ID NO: 341), WETC (SEQ ID NO: 342), KLDGP(SEQ ID NO: 343), WIYPxK (SEQ ID NO: 344), V[HS]DSK (SEQ ID NO: 345),EQCGT (SEQ ID NO: 346), [KE][MVIT]PYA (SEQ ID NO: 347), [DE]xxML[RP]W(SEQ ID NO: 348), YExLHx[FY] (SEQ ID NO: 349), WY[TSN]xEK (SEQ ID NO:350), [YF]H[DNS]AV (SEQ ID NO: 351), DxTG[VI]P (SEQ ID NO: 352), FDxxGEH(SEQ ID NO: 353), QC[AK]xx[HE]C (SEQ ID NO: 354), LW[FY]xPxE (SEQ ID NO:355), C[MI][PA]GxxC (SEQ ID NO: 356), Cxxxx[AVS]ADC(SEQ ID NO: 357),TtESxV (SEQ ID NO: 854), KDV[GA]E(SEQ ID NO: 855), KPxD[FWM]GxK(SEQ IDNO: 856), VxADGT (SEQ ID NO: 857), M[AP][AT]AD (SEQ ID NO: 858),VPxPK[DG](SEQ ID NO: 859), QxKP[TS]D (SEQ ID NO: 860), F[TS]xDGF (SEQ IDNO: 861), Wx[RK]VY[VA] (SEQ ID NO: 862), [CS]T[TS]Exxx[YF] (SEQ ID NO:863), YxETC[TI] (SEQ ID NO: 864) or combinations thereof.

In some embodiments, motifs that are indicative of Borellia burdorferiinfection (Lyme disease) are any one or more of VQQExxxxxP (SEQ ID NO:358), QQEGxxxx[YC] (SEQ ID NO: 359), QEG[IV]Q (SEQ ID NO: 360),G[IV]QxEG (SEQ ID NO: 361), [LI]xxA[ILV]xxRG (SEQ ID NO: 362),[ATNSD]xxxxAl[LAM]xR (SEQ ID NO: 363), Ix[LM]xGFxK (SEQ ID NO: 364),LxGM[RQ]K (SEQ ID NO: 365), [HR]xDxTNxF (SEQ ID NO: 366), [DA]DPTN (SEQID NO: 367), [KR]x[DE]xTNxF (SEQ ID NO: 368), [ET][ML]HKF (SEQ ID NO:369), [ML]xxEFHK (SEQ ID NO: 370), Q[TI]EQxxxxxK (SEQ ID NO: 371),DxSP[IL]E (SEQ ID NO: 372), PFx[AP]YxK (SEQ ID NO: 373), VxxYFxx[LV]xK(SEQ ID NO: 374), KxVDxDR (SEQ ID NO: 375), [DN][AS]A[AG]F (SEQ ID NO:376), Cx[NA]xKFC (SEQ ID NO: 377), Kx[GRST]AE[YF] (SEQ ID NO: 378),HQV[PA]xxx[DHE] (SEQ ID NO: 379), IPxxV[IF]xxR (SEQ ID NO: 380),Cx[ALT]xWEx[CA] (SEQ ID NO: 381), CxxxCA[IL]xxR (SEQ ID NO: 382),I[IV]Ixx[MT]xK (SEQ ID NO: 383), QG[ITL]x[KN][FY] (SEQ ID NO: 384),KxxPl³x1N (SEQ ID NO: 385), G[YF][FY]FxxK (SEQ ID NO: 386), DKNVx[IV](SEQ ID NO: 387), [QE][KR][ND]xSG (SEQ ID NO: 388), K[RK]PGD (SEQ ID NO:389), EGAxQP (SEQ ID NO: 390), GSPEY (SEQ ID NO: 391) or combinationsthereof.

In some embodiments, peptides that are indicative of Borellia burdorferiinfection (Lyme disease) are any one or more of VQQEgaqqqP (SEQ ID NO:392), QEGVQ (SEQ ID NO: 393), GVQqEG (SEQ ID NO: 394), IlkAVveRG (SEQ IDNO: 395), IaaAIvlRG (SEQ ID NO: 396), DqiaaAIAR (SEQ ID NO: 397),AkkmrAlLvR (SEQ ID NO: 398), AenhkAILtR (SEQ ID NO: 399), IkLpGFkK (SEQID NO: 400), IfLeGFlK (SEQ ID NO: 401), LrGMRK (SEQ ID NO: 402), DDPTN(SEQ ID NO: 403), KtDrTNdF (SEQ ID NO: 404), KdDpTNkF (SEQ ID NO: 405),KtDkTNdF (SEQ ID NO: 406), TLHKF (SEQ ID NO: 407), QIEQsststK (SEQ IDNO:408), DlSPIE (SEQ ID NO: 409), PFsAYiK (SEQ ID NO: 410), VkdYFdsLaK(SEQ ID NO: 411), DAAAF (SEQ ID NO: 412), KIRAEF (SEQ ID NO: 413),KsSAEF (SEQ ID NO: 414), KgGAEF (SEQ ID NO: 415), IIIidTsK (SEQ ID NO:416), IIIngMtK (SEQ ID NO: 417), IIItnMeK (SEQ ID NO: 418), QGIiNY (SEQID NO: 419), QGIcNY (SEQ ID NO: 420), KetPPaLN (SEQ ID NO: 421), GFYFifK(SEQ ID NO: 422), DKNVkI (SEQ ID NO: 423), EKNsSG (SEQ ID NO: 424),KKPGD (SEQ ID NO: 425), EGAqQP (SEQ ID NO: 426), GSPEY (SEQ ID NO: 427)or combinations thereof.

In some embodiments, peptides that are indicative of Toxoplasma gondiiinfection are any one or more of HEhEFQ (SEQ ID NO: 428), LDFWrE (SEQ IDNO: 429), LDFWqE (SEQ ID NO: 430), LDMWeE (SEQ ID NO: 431), HCSAC (SEQID NO: 432), FsGVVN (SEQ ID NO: 433), YpGVVN (SEQ ID NO: 434), KgshGRGfi(SEQ ID NO: 435), GPHAE (SEQ ID NO: 436), PRREP (SEQ ID NO: 437), PvPDFS(SEQ ID NO: 438), PvPDFT (SEQ ID NO: 439), PlPDFT (SEQ ID NO: 440),PlPDFS (SEQ ID NO: 441), PaPDFS (SEQ ID NO: 442), NaglEvYAeD (SEQ ID NO:443), NrrrErYGeD (SEQ ID NO: 444), PGAvlLD (SEQ ID NO: 445), PAAskLD(SEQ ID NO: 446), PAAesLD (SEQ ID NO: 447), PGAarLD (SEQ ID NO: 448),PGAldLD (SEQ ID NO: 449), MPSwSnE (SEQ ID NO: 450), MPStSdE (SEQ ID NO:451), MPSeStE (SEQ ID NO: 452), MPSaSpE (SEQ ID NO: 453), RlYvHRS (SEQID NO: 454), RlYrHRT (SEQ ID NO: 455), KgYtHRT (SEQ ID NO: 456),KPpFeFgK (SEQ ID NO: 457), KPgFvFlK (SEQ ID NO: 458), DDSeGaR (SEQ IDNO: 459), DDScGrR (SEQ ID NO: 460), DDSkGdR (SEQ ID NO: 461), DDSsGyR(SEQ ID NO: 462), KeAAgRG (SEQ ID NO: 463), KdASlRG (SEQ ID NO: 464),KgSSgRG (SEQ ID NO: 465), KtSSrRG (SEQ ID NO: 466), KtQTvRG (SEQ ID NO:467), KrSTIRG (SEQ ID NO: 468), DQPEN (SEQ ID NO: 469), GQPEN (SEQ IDNO: 470), KNNDG (SEQ ID NO: 471), RNNDG (SEQ ID NO: 472), NlVGEeY (SEQID NO: 473), NdSGEiY (SEQ ID NO: 474), EPVTG (SEQ ID NO: 475), HGMPK(SEQ ID NO: 476), HGMAK (SEQ ID NO: 477), VPWIF (SEQ ID NO: 478),KsSVpFQ (SEQ ID NO: 479), KeTVnFQ (SEQ ID NO: 480), VWSGS (SEQ ID NO:481), IWSGS (SEQ ID NO: 482), FSLenWG (SEQ ID NO: 483), FSMgrWG (SEQ IDNO: 484), FSLAWG (SEQ ID NO: 485), FSLAWG (SEQ ID NO: 486), FSLtnWG (SEQID NO: 487), PTNQG (SEQ ID NO: 488), PTNPG (SEQ ID NO: 489), RKlhWnHrT(SEQ ID NO: 490), KKyrYrHpT (SEQ ID NO: 491), RKavYqHnT (SEQ ID NO:492), RtlHPRF (SEQ ID NO: 493), HfrHPRF (SEQ ID NO: 494), RvaHPRF (SEQID NO: 495), WqaHPRF (SEQ ID NO: 496) or combinations thereof.

In a related aspect, the invention provides peptide display libraries.The peptide library may comprise random peptide libraries that can beused to identity peptide signatures and motifs. See, e.g., FIG. 1. Inother embodiments, the peptide library may be configured to detectpreviously identified peptide signatures and motifs. See, e.g., FIG. 2Aand FIG. 2B. Such peptide libraries may comprise one or more of themotifs described in the paragraph above.

Kits

Various compositions and reagents useful for the invention describedherein may be provided in kit format. A kit may include, for instance,some or all of the components necessary to carry out the assaysdescribed herein. For instance, the kit may comprise buffers, antibodycapture reagents (e.g., microbeads coupled to Protein A, Protein G,Protein L, or other anti-Ig antibody or aptamers), enzymes (e.g., foramplification and/or sequencing of nucleic acids), instructions and anyother necessary or useful components. The components of the kit may beprovided in any suitable foim, including frozen, lyophilized, or in apharmaceutically acceptable buffer such as TBS or PBS. The kit may alsoinclude a solid support containing a peptide display library (e.g.,microorganisms such as E. coli that express a random peptide library ora peptide library configured for characterizing a phenotype of interest)in any suitable form. The kits may also include other reagents and/orinstructions for carrying out assays such as, for example, flowcytometric analysis, ELISA, immunoblotting (e.g., western blot), andsequencing. Kits may also include components such as containers (e.g.,tubes) and/or slides pre-formatted to containing control samples and/orreagents with additional space (e.g., tubes, slides and/or space on aslide) for experimental samples. The kit may also comprise one or bothof an apparatus for handling and/or storing the sample obtained from theindividual and an apparatus for obtaining the sample from the individual(i.e., a needle, lancet, and collection tube or vessel).

EXAMPLES

Below we present examples of the method to identify motifs and peptidesuseful for the diagnosis of disease. The present method can be appliedto any condition wherein an adaptive immune response occurs includinginfectious, autoimmune, parasitic, allergic, oncological, neurological,cardiovascular, and endocrine diseases and disorders.

Example 1 Celiac Disease—Discovery and Validation of Diagnostic Motifsand Peptides

Celiac disease (CD) is characterized by autoimmunity to wheat, barleyand rye cereal grain proteins, leading to antibody and T-cell mediatedattack of the small intestinal epithelium, and damage to the villi. Theresultant damage impairs adsorption of essential nutrients. Two distinctantibody specificities or types are individually diagnostic for thepresence of CD. Celiac disease is diagnosed by the presence of IgAautoantibodies towards the human tissue transglutaminase antigen TG2, oralternatively by the presence of IgA and/or IgG antibodies towardsdeamidated gliadin peptide epitopes of wheat barley and rye proteins.Diagnostic criteria currently require small intestinal biopsy to confirmdisease. The only available treatment is a strict gluten-free diet.

Patient Samples

A total of 32 celiac disease and 28 control serum samples (500μl/sample) were analyzed. Patients were diagnosed with active celiacdisease based on symptoms and gluten challenge testing, as well as usinga positive result from 1 of the following criteria: 1) small intestinalbiopsies with a Marsh 3a-3c histological lesion, and 2) seropositive fortissue transglutaminase 2 (TG2) and/or endomysial antigen (EMA)autoantibodies. Healthy individuals were asymptomatic for celiac diseaseand tested seronegative for TG2 and EMA autoantibodies. Deamidatedgliadin peptide (dGP) ELISA was also performed for the control anddisease samples.

Sample CD92 was diagnosed as non-celiac after screening was completedtherefore this sample was removed from the CD sample cohort fordownstream analysis. After performing discovery, CD88 was also diagnosedas non-celiac, and having been treated with olmesartan.

Serum samples were stored at −80° C. and aliquoted to reduce freeze/thawcycles. On the day of use, 32 μL were thawed for dilution and remainingserum was marked and re-frozen for future use. Sixteen celiac disease(including CD88) and thirteen control sera were used as an initialdiscovery set. The validation set consisted of fifteen celiac diseasesamples and fifteen control samples (i.e., non-CD).

Experimental Protocol for Celiac Disease Biomarker Discovery

A summary of the general processing and sequencing methods used for theceliac and control serum samples are detailed as follows:

1) Serum depletion step: Antibodies targeting E. coli cells are removedby incubating serum diluted in PBS with an E. coli strain expressing thelibrary scaffold alone. After an overnight incubation, the bacteriaalong with any bound antibodies are removed using centrifugation andcollection of the supernatant (unbound antibodies).

2) Library clearing step: Peptide libraries are first cleared of proteinA and protein G binders by incubating the induced library with magneticbeads coated with protein A and protein G. Magnetic separation capturesthe beads along with any cells that are bound to the protein coating thebeads. The unbound fraction is collected for screening for serumantibody binders.

3) Antibody binding step: Collected (E. coli depleted) serum diluted inPBS is incubated with Protein A and G cleared cells expressing thepeptide library. Antibodies from serum bound to expressed peptides onthe cells are harvested using centrifugation followed by washing withPBST to eliminate non-specific interactions.

4) Library enrichment step: Washed cells are then incubated withmagnetic beads coated with protein A and protein G to capture antibodiesfrom the serum along with the cells expressing peptides the antibodiesare interacting with. The beads are washed 5 times with PBS whilemagnetized to remove cells captured non-specifically.

6) Growth step: The final enriched library (bound to washed beads) isresuspended in Luria broth (LB) and the captured cells are allowed togrow overnight for replication.

7) Repeat enrichment step: This serum antibody-library peptideenrichment step can be repeated a second time to further enrich forpeptide members of the library that interact with antibodies from serumand reduce non-specific binding cells that may have come through thefirst round of the screen. However, a single enrichment step may besufficient.

8) Enrichment analysis step: After the second enrichment is completed,the final enriched library is analyzed by FACS to confirm and quantifybinding of library members to patient serum antibodies.

9) DNA isolation from enriched library step: Plasmid is isolated fromthe enriched library for each serum sample for preparation for deepsequencing analysis.

10) Amplicon preparation step: The region of interest (random/peptideregion from the library) is amplified using the plasmid as template withforward and reverse primers that flank the random region. The primerscontain adaptors specific for use on the Illumina NextSeqnext-generation sequencing platform (Illumina, Inc, San Diego, Calif.).The PCR product is cleaned using magnetic beads that bind DNA and theresulting product is subjected to a second PCR using primers specific tothe adaptors from the first PCR. The primers are provided by theIllumina Nextera XT indexing kit. The second PCR primers contain 8nucleotide indices to provide a unique index combination specific to theamplicon from each sample for tracking of the sample during thesequencing.

11) Amplicon quality control step: After cleaning the second PCRproduct, the purity is confirmed using gel electrophoresis and thequantity of the DNA is determined. Amplicons specific for the enrichedlibraries from all serum samples screened are normalized and pooled atequal molar concentrations for running on the NextSeq instrument.

12) Sequencing step: The amplicon pool is run on the NextSeq instrumentthrough a paid service following instructions from the manufacturer(Illumina). A 75 cycle high-output flow cell is used with single read(“forward” direction) and dual indexing (both 5 prime and 3 primeindices are sequenced). After sequencing is complete, the samples areautomatically de-multiplexed using imputed sample identities withNextera XT indices. These specifications allow for approximately 300million total indexed sequences per run.

13) Sequence de-multiplexing step: Resulting sequences arede-multiplexed using the index codes to identify which serum samples thesequences originated from. Indexed sequences are sorted for each sampleand subjected to bioinformatics analysis.

Sample Analysis via Display-Seq.

Display-seq was used to identify millions of antibody-binding peptidesper specimen as follows. A large high-quality 12-mer peptide library(diversity=8×10⁹), constructed using triplet-phosphoramidites to removestop codons and normalize amino acid frequencies was used. The libraryis self-renewing, and ˜100M unique peptides was determined to establishbaseline statistics, thereby providing a long-term supply of stable,quantified diversity. Before peptide library selection, clinicallycharacterized sera were depleted of E. coli binding antibodies usingcells that display the scaffold without a peptide. Selections wereperformed as described [19, 20]. In brief; after library growth andinduction of expression for display, antibody binding library memberswere enriched using two cycles of magnetic-activated cell sorting (MACS)to >85% pure binders as measured/confirmed using flow cytometry.

E. Coli Specific Serum Antibody Depletion.

To remove E. coli binding antibodies from serum samples prior to libraryscreening, an induced culture of cells expressing the library scaffoldalone (eCPX) was incubated with diluted sera. Escherichia coli strainMC1061 [FaraΔ 139 D(ara-leu)7696 GalE15 GalK16 Δ (lac)X74 rpsL (StrR)hsdR2 (rK−mK+) mcrA mcrB1] was used with surface display vectorpB33eCPX. eCPX cultures grown overnight at 37° C. with vigorous shaking(250 rpm) in LB (10 g tryptone, 5 g yeast extract, 10 g/L NaCl)supplemented with 34 μg/mL chloramphenicol (CM) and 0.2% glucose werecollected by centrifugation, inoculated in fresh LB+CM, grown to anOD₆₀₀=0.6, and induced for 1 hr at 37° C. with 0.02% wt/volL(+)-arabinose. After induction, the cells were centrifuged at 3,000relative centrifugal force (rcf) for 5 min., washed once with cold PBST(PBS+0.1% Tween 20), and resuspended in 1 mL PBS containing serumdiluted 1:25 (1×10⁶ cells per μL depletion sample). Samples wereincubated overnight at 4° C. with gentle mixing on an orbital shaker (20rpm). Antibodies that bound to E. coli or the eCPX scaffold were removedby centrifugation of the incubated culture at 5,000 rcf for 5 min.twice, recovering the serum supernatant after each centrifugation. Thedepleted serum was stored at 4° C. for up to 2 weeks during use.

Bacterial Display Library Screening.

An X12 bacterial display library was used to screen and isolate peptidebinders to antibodies in individual serum samples through two rounds ofselection.

First Round Selection Using Magnetic Assisted Cell Sorting (MACS):

The first selection round employed MACS to enrich the library forantibody binding peptides. A frozen aliquot of the X12 librarycontaining 1×10¹¹ cells (10× the expected diversity) was thawed andinoculated into 500 mL LB+CM. After growth to an OD₆₀₀=0.6 at 37° C.with 250 rpm shaking, the cells were induced with 0.02% wt/volL(+)-arabinose for 1 hour using the same growth conditions. Cells(1×10¹¹ per sample) were collected by centrifugation (3,000×g for 10min.) and resuspended in 1 mL cold PBS. Prior to incubation with serum,cells were cleared of peptide clones that bind proteins A/G byincubating cells with washed protein A/G magnetic beads (Pierce) at aratio of one bead per 50 cells for 45 min. at 4° C. with gentle mixing.Magnetic separation for 5 min. (×2) was used to recover the unboundcells. Recovered cells from the supernatant were centrifuged,resuspended in 500 μL diluted sera (1:25 in PBS), and incubated for 45min. at 4° C. with gentle mixing. Following serum incubation, cells werewashed by centrifugation, and resuspended in 1 mL cold PBST (×3). Afterthe final resuspension, washed protein A/G magnetic beads were added ata ratio of one bead per 50 cells. After a 45 min. incubation withprotein A/G beads at 4° C. with gently mixing, a second magneticseparation was performed to isolate cells expressing peptides that bindto serum antibodies. The supernatant (unbound cells) was discarded andthe separated cells/beads were washed with 1 mL cold PBST. Five repeatwashes were performed while the tube was being magnetized. After thelast wash, the beads were resuspended in 1 mL of LB and inoculated into25 mL LB+CM+glucose to suppress expression. The flask was grownovernight at 37° C. with shaking at 250 rpm. A 10 uL sample was removedprior to inoculation for dilution and plating on LB-agar to estimate thediversity of the enriched library.

Second Round Selection Using Magnetic Assisted Cell Sorting (MACS):

A second round of affinity selection was carried out using MACS tofurther enrich the library for antibody binding peptides. Afterovernight growth of the first round MACS enriched library, cells wereinoculated (>20× estimated diversity) at 1:50 into 10 mL LB+CM and grownto an OD₆₀₀=0.6. After induction with arabinose for 1 hour, a volume ofcells>20× the library diversity was centrifuged and resuspended in 100□L cold PBST. Prior to incubation with serum, cells were cleared againof peptide clones that bind protein A/G by incubating cells with washedprotein A/G magnetic beads (Pierce) at a ratio of one bead per cell for45 min. at 4° C. with gentle mixing. After clearing the cells of proteinA/G binding peptides, the library was incubated with 100 μL diluted sera(1:25 in PBS) for 45 min. at 4° C. Following serum incubation, cellswere washed by centrifugation, and resuspended in 100 μL cold PBST (×3).After the final resuspension, washed protein A/G magnetic beads wereadded at a ratio of one bead per cell. After a 45 min. incubation withprotein A/G beads at 4° C. with gently mixing, a second magneticseparation was performed to isolate cells expressing peptides that bindto serum antibodies. The supernatant (unbound cells) was discarded andthe separated cells/beads were washed with 500 μL cold PBST. Five repeatwashes were performed while the tube was being magnetized. After thelast wash, the beads were resuspended in 1 mL of LB and inoculated into10 mL LB+CM+glucose to suppress expression. The flask was grownovernight at 37° C. with shaking at 250 rpm. A 10 uL sample was removedprior to inoculation for dilution and plating on LB-agar to estimate thediversity of the enriched library.

Analysis of Enriched Library Using Fluorescence Activated Cell Sorting(FACS):

The following day, cells were analyzed for reactivity to the individualserum they were screened against to assess enrichment levels via FACS.After overnight growth of the MACS×2 enriched library (i.e., the libraryafter the two rounds of MACS described above; “MACS×2”), cells wereinoculated (>20× estimated diversity) at 1:50 into 5 mL LB+CM and grownto an OD₆₀₀=0.6. After induction with arabinose for 1 hour, a volume ofcells>20× the library diversity was centrifuged and resuspended in 50 □Ldiluted sera (1:25 in PBS) for 45 min. at 4° C. Cells were washed asdescribed in the second round enrichment section (100 uL PBST) andresuspended in □-IgA-PE diluted 1:200 in 100 □L cold PBS. Following a 45min. incubation at 4° C., the cells were washed again and finallyresuspended in 500 μL PBS for FACS sorting. Cells were analyzed for % ofthe cells with fluorescence signal greater than background (eCPXscaffold) by setting a gate to exclude 99% of the signal from serumincubated with cells containing eCPX scaffold lacking peptide (negativecontrol). Libraries with ˜80% or greater enrichment (percent of cellsthat are above background/percent of peptides that bind serumantibodies) were processed for deep sequencing analysis (next-generationsequencing; NGS).

Enrichment Analysis.

The majority of samples demonstrated >90% enrichment values (percentabove background) with the lowest enrichment values at ˜78%. Incontrast, the background binding (eCPX scaffold percent abovebackground) is minimal. The majority of the samples have backgroundbinding at <1% with the highest background at 3.4%. These datademonstrate the MACS×2 enrichment strategy effectively isolated apopulation of cells that express peptides that bind to serum antibodiesand that this procedure collects minimal background (non-specific)binding cells.

Serum dilutions of 1:25 were used in this Example to maximize coverageof the repertoire (including lower titer antibodies), and tosimultaneously minimize antibody-mediated cell death (e.g. due toresidual complement activation), and non-specific binding. However,serum may be used at any appropriate dilution, including withoutdilution, as desired. Plasmid DNA was isolated from each enrichedspecimen-specific library, and used to generate bar-coded amplicon DNAlibraries using a two-step PCR with the Illumina Nextera index kit.Amplicon preparations were cleaned using Ampure beads, diluted to afinal concentration of 4 nM each for library pooling and sequenced onthe Illumina NextSeq 500 1×75 high-output flow cell. To maximize thenumber of usable reads obtained, we used a i) forward primer in thefirst PCR step having five degenerate bases, and ii) using 30% spikedPhiX reference DNA. At least one reference specimen from one healthyindividual was included in each NGS run to quantify run-to-runvariability in read depth and quality, and longitudinal assay stabilityover 10 months.

Amplicon Preparation and Next Generation Sequencing on the IlluminaPlatform:

Amplicon Preparation: Cells grown overnight after the second round ofMACS sorting were collected and plasmid was extracted using a plasmidminiprep kit (Qiagen). The random peptide region was amplified using atwo-step PCR. For the first PCR step, the primers included adaptorsspecific to the Illumina platform with annealing regions that flank therandom section (peptide library) of the eCPX scaffold (sequencesindicated below):

Forward Primer:

(SEQ ID NO: 870) TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGnnnnn CCAGTCTGGCCA GGG.Bold and underlined region is the annealing region. nnnnn is 5 randomdegenerate bases.

Reverse Primer:

(SEQ ID NO: 871) CCAGTACTACGGCATCAC TGCTGTCTCTTATACACATCTCCGAGCCCACGAGAC.Bold and underlined region is the annealing region.

Products from the first PCR were purified after 25 rounds of PCRamplification (65° C. annealing temp) using Agencourt Ampure XP (BeckmanCoulter) clean up beads. Resulting product was subjected to a secondround of PCR using Illumina Nextera XT indexing primers. These primersprovide unique 8 base pair indices on the 3 prime and 5 prime ends ofthe amplicons for tracking the sequences back to the sample used forscreening and amplicon preparation. Amplicons were cleaned up as beforeafter 12 rounds of PCR amplification (70° C. annealing temp). The finalPCR product (amplicon) was analyzed using a DNA high sensitivity chip ona Bioanalyzer 2100 (Agilent) for purity, and DNA concentration wasmeasured using DNA high sensitivity reagent on a Qbit instrument (LifeTechnologies). All samples were normalized to 4 nM and pooled togetherinto a sequencing library.

Sequencing on Illumina NextSeq:

After quantification quality control of the pool was performed, thesample was diluted and loaded on to the NextSeq instrument. A 75 cyclehigh-output flow cell was used with single read (one direction) and dualindexing (both 5 prime and 3 prime indicies are sequenced). Aftersequencing was complete, the samples were automatically de-multiplexedusing imputed sample identities with Illumina Nextera XT indicies.

NGS Quality Control

After construction, each amplicon was run on an agarose gel to confirmamplification of the correct product (254 bp) and absence ofcontaminating bands. Amplicons were quantified and pooled at a finalconcentration of 4 nM. The final amplicon pool was run on thebioanalyzer as a second quality control (QC) step to confirm the poolrepresented a single amplified band of the appropriate DNA size andconcentration.

NGS Results

NGS results are summarized using data provided from Illumina BaseSpacesoftware and from bioinformatics results using a computational algorithmfor peptide motif discover in NGS datasets (hereafter refered to as“IMUNE”). The overall run summary indicates the “quality” of the fullrun in terms of number of sequences, the average number of sequencesreturned for each patient, and the standard deviation (SD) of thesequences for each patient. Low patient sequences (and total sequences)suggest potential problems with a sequencing run and may trigger repeatsequencing of that pool. A large SD for the sequences indicate poorpooling and may trigger a new quantification measurement and poolcreation for a repeat sequencing run. Sequences that are read andassigned to a sample on BaseSpace must meet further quality controlcriteria for IMUNE. This is noted by comparing the total sequences givenby BaseSpace to the total given by IMUNE for each sample. Consistently,˜94% of the indexed sequences for a given sample are recognized byIMUNE. The remaining sequences are often too short (<36 base pairs) tomatch correctly with an X12 peptide that is displayed. As a result,shorter sequences are filtered and not used for downstream motifanalysis. At least 3 million total sequences were obtained from NGS foreach CD specimen.

Bioinformatic Analysis Identification of Celiac-Specific Motifs UsingIMUNE Software

Motif discovery algorithms that utilize pairwise sequence comparisonsare not amenable to large NGS datasets such as created by theDisplay-Seq discovery platform. For instance, motif discovery in 10,000peptides using the MEME algorithm can require one week on a singleprocessor, and computation time scales more than quadratically. Toaddress this limitation, we developed a computational algorithm forIdentification of Motifs Using Next-generation sequencing Experiments(IMUNE). IMUNE calculates the enrichments of all possible 4, 5, and 6amino acid patterns (˜8.5 billion) in a window of 10 positions,identifies patterns that are significantly enriched (p<0.001), andclusters these patterns using the PAM30 similarity scoring matrix tobuild motifs.

IMUNE was used to identify patterns and motifs specific to celiacsamples in the discovery set. The discovered motifs were dominated bygliadin motif variants as these sequences were the most abundant in theceliac samples and absent in the control samples. The gliadin motifvariants can be mapped to a single gliadin peptide QPEQPFPE. The 8-mergliadin motif encompasses all the gliadin variant motifs obtained frombioinformatics analysis by sequence alignment and clustering.

Using either IMUNE or MEME 79 redundant motifs were discovered. The 79redundant motifs associated with gliadin variants clustered into 4motifs. Diagnostic motifs for Celiac Disease include namely QXXXPF[PS]E(SEQ ID NO: 6), PFSEM (SEQ ID NO: 7), PFSEX[FW] (SEQ ID NO: 8),QPXXPFX[ED] (SEQ ID NO: 4).

Motif Analysis in Validation Sample Set

The motifs discovered using the discovery set were further analyzed inthe validation sample set. Enrichment values in the validation set forthe motifs from IMUNE analysis are shown in FIG. 5. Of note, the panelof independent (non-gliadin) motifs performed poorly in the validationsample set while the gliadin variant motifs performed well.

IMUNE and MEME both identified gliadin variant motifs that weresensitive and specific in the validation sample set. The non-gliadin(additional) motifs from both IMUNE and MEME analysis failed to validateand are likely artifacts of common motifs that demonstrated enrichmentin the discovery celiac samples.

Both IMUNE and MEME identified multiple motifs that were specific (i.e.occur in <1% of non-celiacs) and sensitive (i.e., in >95% of individualswith celiac disease) to celiac disease and that also correspond to asingle gliadin motif.

In FIG. 5 enrichments for all samples were used to calculate z-scoresfor each motif in the 4-gliadin motif panel (a=IMUNE and b=MEME). Eachz-score indicates the enrichment value minus the mean enrichment for allsamples divided by the standard deviation of all samples. The summedz-scores are graphed comparing celiac samples to control and additionalsamples with datasets archived in HASRD. Note the IMUNE panel wouldcorrectly diagnose all celiac cases and the two additional samples whilethe MEME panel would misdiagnose two celiac samples and four additionalsamples. The celiac diagnostic panel generated by IMUNE was 100%sensitive (31 of 31 celiac samples are positive) with a specificity ofat least 99.6% (2 of 456 control samples are positive). These twopositive specimens may be from individuals with celiac disease.

Example 2 Discovery of Motifs Diagnostic of Chagas Disease

Chagas disease, also known as American trypanosomiasis, is a tropicalparasitic disease caused by the protozoan Trypanosoma cruzi (T. cruzi).It is mainly spread by insects known as Triatominae, or kissing bugs,but may also be spread through blood transfusion, organ transplantation,contaminated food, and by vertical transmission from mother to fetus.Medication is effective if given early. However, most people infectedwith the disease do not realize they have the disease and treatmentbecomes less effective the longer a person has had Chagas disease.Untreated, Chagas can result in death.

Patient Samples

Serum samples (100 μl/sample) from 30 confirmed Chagas patients and 30confirmed healthy donors were provided by the United States Center forDisease Control (CDC). Chagas diagnosis was made on the basis of twoserological tests, the Wiener Chagatest ELISA and the CDC LaboratoryDeveloped Test (LDT) TESA-Immunoblot. If both tests produceddiscrepancy, a third immunofluorescence assay was used as a tie-breakertest. Serum samples were stored at −80° C. upon receipt and thawed onthe day of use.

Experimental Protocol for Chagas Disease Biomarker Discovery

Experiments were performed as described in Example 1.

Serum was diluted 1:25 in PBS at the E. coli depletion step andmaintained at 4 Deg C. after depletion. For standard ecpx depletion, 1mL each of E. coli cells induced to express ecpx 357 and 428 scaffolds(2 mL total) was used/ul of neat serum for depletion. Both MACS stepswere performed at a 1:25 final serum dilution.

FACS Analysis of Enrichment of Chagas and Control Serum after MACS×2 forDiscovery and Down Selection

The effective removal of E. coli antibodies and the reactivity of eachserum sample to its enriched library pool were analyzed by Flowcytometry as a quality control step in the screening process. Samplesgenerally exhibit≥75% reactivity of above background indicating that thelibraries are highly enriched for patient specific peptides.

NGS Quality Control

Each amplicon was run on an agarose gel to confirm amplification of thecorrect product (254 bp) and absence of other bands representingnon-specific PCR products. Amplicons were quantified and pooled at afinal concentration of 4 nM each. The final amplicon pool was run on thebioanalyzer as a second QC step to confirm the pool represented a singleamplified band of the appropriate amplicon concentration.

NGS Results

NGS raw sequence data from BaseSpace provides a breakdown of the totalsequences obtained for each patient based on their unique barcodeidentifier. In the initial IMUNE processing step, sequences that met thequality criteria including: 1) upstream and downstream annealing regionscontain ≤25% insertions, deletions and/or mutations, 2) the randomregion is of the expected length 3) no base throughout the read isunassigned (i.e. N). Unique reads are the number of sequences perpatient after removal of duplicates, combination of similar sequenceswith few mutations (i.e. 3 or fewer) and removal of sequences thatcontain stop codons. The percentage of sequences that meet the abovecriteria relative to the total number of raw sequences is anothermeasure of the quality of the NGS run. After processing, ˜95% of the rawsequences from Basespace for each patient contain useable sequenceinformation.

Bioinformatic Analysis

Disease specific motifs were identified using MEME and IMUNE asdescribed in Example 1.

Preliminary IMUNE analysis of the discovery set epitope repertoires from30 Chagas and 30 control sera discovered 1476 non-redundant motifs. Ofthose we considered the 200 motifs constructed using the largest numberof contributing patterns.All of those motifs were specific and sensitiverelative to the Chagas controls. We used HASRD (see Example 1) as adown-selection tool to identify motifs that were highly specific forChagas based on their lack of enrichment in ˜300 additional “control”samples. Additionally, we removed motifs that, while non-redundant werevariations on the same epitope. This process revealed at least 39distinct Chagas-specific motifs with varying sensitivities for Chagasdisease in the discovery set Table 1.

TABLE 1Motifs and peptides comprising panel for the diagnosis of Chagas panelID Panel motif Antigen(s); peptide sequence(s)  1[RK]MRxID (SEQ ID NO: 104)  2 QHxGHP (SEQ ID NO: 105)Glutathione peroxidase, 60S ribosomal protein L2;QHkGHP (SEQ ID NO: 143), QHiGHP (SEQ ID NO: 144)  3KxxLPED (SEQ ID NO: 106)Gim5A protein, Phosphatidylinositol kinase domainprotein, Dynein intermediate chain, Trans-splicingfactor, G-actin binding protein; KalLPED (SEQ ID NO:145), KkhLPED (SEQ ID NO: 146), KitLPED (SEQ IDNO: 147), KtiLPED (SEQ ID NO: 148), KvlLPED (SEQ ID NO: 149)  4[IV]LxxFGY (SEQ ID NO: 107)60S ribosomal protein L13a, DNA polymerase, Alpha-adaptin, Mucin-associated surface protein (MASP);VLkkFGY (SEQ ID NO: 150), VLhlFGY (SEQ ID NO:151), VLgeFGY (SEQ ID NO: 152), VLepFGY (SEQ ID NO: 153)  5PLDxxxxIS (SEQ ID NO: 108)Kinesin, Kinetoplast-associated protein Tcp22;PLDvekeIS (SEQ ID NO: 154), PLDllkyIS (SEQ ID NO: 155)  6ETXIPXE (SEQ ID NO: 109)Complement regulatory protein, Trans-sialidase, FL-160-1 epitope, OSM3-like kinesin; ETkIPsE (SEQ IDNO: 156), ETeIPsE (SEQ ID NO: 157), ETgIPfE (SEQ ID NO: 158)  7[VI]Nx[DE][ML]YxP (SEQ ID40S ribosomal protein S21; VNvDLYiP (SEQ ID NO: NO: 110) 159)  8FLxxIGA (SEQ ID NO: 111) Flagellum-Associated Protein, Membrane protein,Dispersed gene family protein 1 (DGF-1), 60Sribosomal protein L14; FLgaIGA (SEQ ID NO: 160),FLlfIGA (SEQ ID NO: 161), FLkaIGA (SEQ ID NO: 162)  9D[VI]x[MI][ILV]x[KR] (SEQ ID UDP-GlcNAc:polypeptide N- NO: 112)acetylglucosaminyltransferase, Oculocerebrorenal Lowesyndrome protein, Dynein heavy chain, cytosolic, R27-2 protein, Myosin heavy chain; DIkMIeR (SEQ ID NO:163), DIiIVsR (SEQ ID NO: 164), DVhMLvR (SEQ IDNO: 165), DVdILeR (SEQ ID NO: 166) 10 RxSPYx[IL]F (SEQ ID NO: 113)Kinetoplast DNA-associated protein 3; RvSPYsIF (SEQ ID NO: 167) 11VGPRH (SEQ ID NO: 114) Microtubule associated protein homolog, AntigenDNA; VGPRH (SEQ ID NO: 168) 12 PQxQH[ED] (SEQ ID NO: 115)Helicase, putative, Phosphatidylinositol 3-kinase;PQkQHE (SEQ ID NO: 169), PQgQHD (SEQ ID NO: 170) 13PxxGGFG (SEQ ID NO: 116) 14 KxEGxxMG (SEQ ID NO: 117)60S ribosomal protein L6, Adenosine 5′-monophosphoramidase; KsEGefMG (SEQ ID NO: 171),KdEGlaMG (SEQ ID NO: 172) 15 KxxGxTxxLS (SEQ ID NO: 118)85 kDa surface antigen, Trans-sialidase-like protein,Glycoprotein 82 kDa; KdnGsTwsLS (SEQ ID NO: 173),KddGsTwaLS (SEQ ID NO: 174) 16 EMG[FW]Q (SEQ ID NO: 119) 17[VI]KxGxxDxP (SEQ ID NO: 120)ADP, ATP carrier protein 1, mitochondrial; IKqGrlDrP (SEQ ID NO: 175) 18PE[DN]ExYP (SEQ ID NO: 121) 19 HYEWA (SEQ ID NO: 122)Lanosterol cyclase, Terpene cyclase/mutase familymember; HYEWA (SEQ ID NO: 176) 20 [HR]SNMxF (SEQ ID NO: 123) 21M[TV]GXXYE (SEQ ID NO: 124) Lanosterol cyclase, 3-methylcrotonoyl-CoAcarboxylase beta subunit; MVGehYE (SEQ ID NO:177), MVGkaYE (SEQ ID NO: 178) 22 Dxx[KH]ExxLL (SEQ ID NO: 125)40S ribosomal protein S8, Neurobeachin/beige protein,Kinesin, ATP-dependent DNA helicase;DqlKEgrLL (SEQ ID NO: 179), DvvKElmLL (SEQ IDNO: 180), DleKEneLL (SEQ ID NO: 181), DldKEvsLL (SEQ ID NO: 182) 23RxxWx[EDA]x[IV][AR] (SEQ ID40S ribosomal protein S3a-1, Dynein heavy chain, NO: 126)Protein kinase, Eukaryotic translation initiation factor4E (EIF4E) interacting protein, AAA ATPase; Mucin-associated surface protein (MASP); RhqWyAvVA (SEQID NO: 183), RhsWfDdVR (SEQ ID NO: 184),RkeWyDvVA (SEQ ID NO: 185), RdrWtEsIA (SEQ IDNO: 186), RatWlDqVR (SEQ ID NO: 187), RyvWnEwVA (SEQ ID NO: 188) 24PxDxxAx[GPA][TS] (SEQ ID NO:Shed-acute-phase-antigen, Translation factor GUF1 127)homolog 1, mitochondrial, Trans-sialidase, Mucin-associated surface protein (MASP), Mucin TcMUCII;PvDstAhGT (SEQ ID NO: 189), PlDcpAlGS (SEQ IDNO: 190), PaDssAhGT (SEQ ID NO: 191),PkDvkAtGS (SEQ ID NO: 192), PpDvsAsGT (SEQ IDNO: 193), PgDlpAkAT (SEQ ID NO: 194),PaDvsAqAT (SEQ ID NO: 195), PpDvpAsGT (SEQ ID NO: 196) 25 PDxxSxT[ARG](SEQ ID NO: 128) UDP-GlcNAc:PI a1-6 GlcNAc-transferase, Small GTP-binding protein RAB6, 90 kDa surface protein, MucinTcMUCII; PDpaSiTA (SEQ ID NO: 197),PDasSsTA (SEQ ID NO: 198), PDsrSiTA (SEQ ID NO:199), PDsrSvTA (SEQ ID NO: 200), PDskSpTA (SEQID NO: 201), PDseSpTA (SEQ ID NO: 202) 26 GRExDG (SEQ ID NO: 129)Mucin-associated surface protein (MASP),Trypanothione synthetase-like protein; GREsDG (SEQID NO: 203), GREaDG (SEQ ID NO: 204) 27 GVPGxxxK (SEQ ID NO: 130)60S ribosomal protein L18, Calpain-like cysteinepeptidase; GVPGshaK (SEQ ID NO: 205), GVPGcviK (SEQ ID NO: 206) 28[LM]xxx[EDQ]VxxIM (SEQ IDSterol 14-alpha demethylase, 60S ribosomal protein L4, NO: 131)GTP-binding protein, Stress-induced protein sti1;LsprEVytIM (SEQ ID NO: 207), LtntDVtrIM (SEQ IDNO: 208), LedeDVlqIM (SEQ ID NO: 209), MadpEVaaIM (SEQ ID NO: 210) 29SxxxVSGG (SEQ ID NO: 132)Putative surface protein TASV-B-25, Aquaporin-likeprotein, Mucin-associated surface protein (MASP),Calcium-transporting ATPase; SqadVSGG (SEQ IDNO: 211), SvgsVSGG (SEQ ID NO: 212),SpsgVSGG (SEQ ID NO: 213), SwfdVSGG (SEQ ID NO: 214) 30A[KR]AG[DN]K (SEQ ID NO: 133) 31 F[RN]xIN[RQ] (SEQ ID NO: 134)Dynein heavy chain, Eukaryotic translation initiationfactor 3 subunit 8; FRiINQ (SEQ ID NO: 215), FRaINR (SEQ ID NO: 216) 32YXPVXPXSY (SEQ ID NO: 135) 33 KxTFPD (SEQ ID NO: 136)Trans-sialidase, Neurobeachin/beige protein;KqTFPD (SEQ ID NO: 217), KaTFPD (SEQ ID NO: 218) 34PFM[FVM]xxR (SEQ ID NO: 137)Cation-transporting ATPase; PFMVqmR (SEQ ID NO: 219) 35EFWEP (SEQ ID NO: 138) 36 [FY]GALS (SEQ ID NO: 139)Kinetoplast-associated protein Tcp22, Protein kinase,ABC transporter; FGALS (SEQ ID NO: 220), YGALS (SEQ ID NO: 221) 37PxGTEN (SEQ ID NO: 140)Trypomastigote small surface antigen; PsGTEN (SEQ ID NO: 222) 38Gx[KE]PWE (SEQ ID NO: 141) Metacaspase; GfKPWE (SEQ ID NO: 223) 39D[IV]Tx[YF][WN] (SEQ ID NO:Intraflagellar transport protein component, Cyclophilin- 142)like protein; DITdYN (SEQ ID NO: 224), DVTgFN (SEQ ID NO: 225)

Of the final 39 motifs that comprise the panel, IMUNE identifiedtwenty-six motifs that were highly sensitive and specific to Chagas thatwere not discovered by MEME. In particular, these included motifs withgreater than 40% sensitivity in the Chagas discovery set.

Panel Development

Two methods were used to generate a panel of motifs that are diagnosticfor Chagas disease. In the first method, the average enrichment andstandard deviation for the 33 motifs in 416 non-Chagas samples werecalculated. A positive signal in a motif is at least 4 standarddeviations above the controls. A patient is diagnosed as positive forChagas if they have a positive signal in at least 3 motifs,indeterminate if they are positive for two motifs and negative if theyare positive in one or fewer motifs. Using these criteria, all thirtyChagas disease samples were positive (FIG. 6) and all the Chagascontrols were negative. Additionally, all 460 controls in HASRD not usedfor discovery were also negative. In the second method, the sum of the zscores is calculated for all motifs and a cut off is determined based onthe desired sensitivity and specificity. As shown in FIG. 6, using a cutoff of 23 yields a sensitivity of 100% and a specificity of 99.5% forall 30 Chagas disease samples and all 460 controls.

Mapping of Chagas Motifs to Trypansoma Cruzi Antigens

Motifs identified by IMUNE often carry sufficient information content toidentify organisms, antigens, and epitopes without prior knowledge ofwhich organism or antigens may be important. About 80% of motifs thatIMUNE identified that were sensitive and specific could be associatedwith a single T. cruzi antigen epitope, by performing degenerate motifsearches within the entire Swissprot/TrEMBL databases using Scanprosite.See Table 1. Notably, i) three antigens (Surface antigen-2, microtubuleassociated protein, and small surface antigen/mucin-like protein) havebeen validated previously, several epitopes were from ribosomalproteins, one ribosomal epitope is identical between T. cruzi andLeishmania sp, an organism that generates false positives in availableChagas tests. The majority of Chagas antigens are novel and have notbeen described or characterized previously.

Example 3 Discovery of Motifs for the Diagnosis of Lyme Disease(Borrelia Burgdorferi Infection)

Lyme disease, also known as Lyme borreliosis, is an infectious diseasecaused by bacteria of the Borrelia genus. Lyme disease is transmitted tohumans by the bite of infected ticks. Diagnosis is based upon acombination of symptoms, history of tick exposure, and possibly testingfor specific antibodies in the blood. However, blood tests are oftennegative in the early stages of the disease. If untreated, symptoms mayinclude loss of the ability to move one or both sides of the face, jointpains, severe headaches with neck stiffness, and heart palpitations.Symptoms can persist for months after treatment and may reoccur yearslater. The disease affects several hundred thousand people a year in theUnited States.

Patient Samples

Serum samples (100 ul/sample) from 20 confirmed late stage Lyme patients(L1-20) with Lyme Arthritis and 20 controls (L21-40) were provided. Lymediagnosis was made on the basis of 2-tier testing via RIBA with reflexto Western blot. Serum samples were stored at −80° C. upon receipt andthawed on the day of use.

Experimental Protocol for Lyme Disease Biomarker Discovery

Experiments and analysis were as described in Example 1.

Serum was diluted 1:25 in PBS at the E. coli depletion step andmaintained at 4 ° C. after depletion. For standard ecpx depletion, 1 mLeach of E. coli cells induced to express eCPX 357 and 428 scaffolds (2mL total) was used per microliter of neat serum for depletion. Both MACSsteps were performed at a 1:25 final serum dilution.

FACS Analysis of Enrichment of Lyme and Control Serum After MACS×2 forDiscovery and Down Selection

The effective removal of E. coli antibodies from serum and the effectiveenrichment of serum antibody binders after two rounds of MACS (M2) wasanalyzed by Flow cytometry as a quality control step in the screeningprocess. Samples generally exhibit≥75% reactivity of above background toM2 library pool, indicating that the libraries are highly enriched forpatient-specific peptides.

NGS Quality Control

Each amplicon was run on an agarose gel to confirm amplification of thecorrect product (254 bp) and absence of other bands representingnon-specific PCR products. Amplicons were quantified and pooled at afinal concentration of 4 nM each. The final amplicon pool was run on thebioanalyzer as a second QC step to confirm the pool represented a singleamplified band of the appropriate amplicon concentration. Half of thedisease set and half of the control set sequenced per run (20 samplesper chip).

NGS Results

NGS raw sequence data from BaseSpace provides a breakdown of the totalsequences obtained for each patient based on their unique barcodeidentifier. In the initial IMUNE processing step, sequences that met thequality criteria including: 1) upstream and downstream annealing regionscontain ≤25% insertions, deletions and/or mutations, 2) the randomregion is of the expected length 3) no base throughout the read isunassigned (i.e. N). Unique reads are the number of sequences perpatient after removal of duplicates, combination of similar sequenceswith few mutations (i.e. 3 or fewer) and removal of sequences thatcontain stop codons. The percentage of sequences that meet the abovecriteria relative to the total number of raw sequences is anothermeasure of the quality of the NGS run. NGS runs for the 60 Lyme andcontrol samples typically resulted in more 5-12 million total sequences,and 2-5 million unique sequences. After processing, ˜95% of the rawsequences from Basespace for each patient contain useable sequenceinformation.

Bioinformatic analysis was performed as described in Example 1.

Identification of Lyme-Specific Motifs Using IMUNE Software

Motif discovery algorithms that utilize pairwise sequence comparisonsare slow and not amenable to the large NGS datasets created by themethods described herein. For instance, motif discovery in 10,000peptides using the MEME algorithm can require one week on a singleprocessor, and computation time scales more than quadratically. Toaddress this limitation, a computational algorithm for Identification ofMotifs Using Next-generation sequencing Experiments (IMUNE) wasdeveloped. IMUNE calculates the enrichments of all possible 4, 5, and(optionally) 6 amino acid patterns (˜8.5 billion) in a window of 10positions, identifies patterns that are significantly enriched (e.g.,p<0.001), and clusters these patterns using a similarity scoring matrix(e.g., PAM30) to build motifs.

Identification of Lyme-Specific Motifs Using MEME

MEME is currently the dominant tool in motif finding. We wished todetermine whether IMUNE outperforms MEME in terms of the number andspecificity of the disease motifs it identifies. For the MEME motifdiscovery, we compiled a list of all peptides that appeared in at least11 Lyme disease samples and in zero controls samples. MEME was used toanalyze the top 4980 of these peptides that appeared in these Lymesamples, to identify the motifs in Table 30.

Candidate Motifs Lyme Motifs Discovered by IMUNE

Preliminary IMUNE analysis of the discovery set epitope repertoires from20 Lyme and 20 control sera discovered 296 non-redundant motifs thatwere at least 40% sensitive and 100% specific. To identify a subset ofthese motifs that together are 100% sensitive and specific for Lymedisease following steps were performed:

1) Down-Selection of Motifs Based on Specificity Using HASRD

We used a database containing hundreds of distinct epitope repertoires(i.e., peptide datasets) as a down-selection tool to identify motifsthat were highly specific for Lyme disease based on their lack ofenrichment in 636 additional untested, non-Lyme samples. Twenty-eightmotifs were highly specific for Lyme disease (significant enrichment in≤2 of the 20 Lyme controls and 636 additional non-Lyme controls (FIG.7)) and were considered for further analysis.

2) Grouping of Motifs into Families

Many of the motifs, while non-redundant, were variations on the sameepitope and thus were grouped together into families. At least 16 Lymespecific motif families were identified.

3) Down-Selection Based on Motif Sensitivity and Patient Coverage

We further down-selected the motifs based on sensitivity and patientcoverage. If two highly specific motifs were present in the same family,the motif that demonstrated the highest sensitivity was selected. Motifsfrom each family were compared to identify those that captured distinctpatient subsets. Of the initial 27 motifs we considered, the final panelincludes 14 motifs, each from a distinct motif family, that togetherexhibit the greatest breadth of patient coverage. A sample wasconsidered positive for any motif if it was >4 standard deviations (SD)above the mean of the controls, indeterminate if it was >3 SD andnegative if it was less than 3 SD.

Lyme Motifs Discovered Using MEME

MEME identified a total of twenty-five motifs. To evaluate theperformance of the two algorithms, MEME motifs were compared with allIMUNE motifs. Of the twenty-five motifs, eight were redundant within theMEME list. IMUNE identified all of the 17 remaining motifs. See Table 2.Thus, IMUNE identified 15/15 of the motifs identified by MEME.

In contrast, of the final 14 motifs that comprise the panel, IMUNEidentified five motifs that were highly sensitive and specific to Lymethat were not discovered by MEME. In particular, these included motifswith ≤60% sensitivity in the Lyme discovery set.

Panel Development

Two methods were used to generate a panel of motifs that are diagnosticfor Lyme disease. In the first method, the average enrichment andstandard deviation for the 14 motifs in 419 non-Lyme samples werecalculated. A positive signal in a motif is at least 4 standarddeviations above the controls. A patient is diagnosed as positive forLyme if they have a positive signal in at least 3 motifs, indeterminateif they are positive for two motifs and negative if they are positivefor one or fewer motifs. Using this criteria, all twenty late Lymedisease samples in the discovery set were positive and all the non-Lymecontrols were negative. Additionally, 636 Disease controls not used fordiscovery were also negative.

In the second method, the sum of the z scores is calculated for allmotifs and a cut off is determined based on the desired sensitivity andspecificity. Using a cut off of 30 yields a sensitivity of 100% and aspecificity of 100% for all 20 Lyme disease samples and all 419controls.

Mapping of Lyme Motifs to Putative Borrelia Burgdorferi Antigens

Motifs identified by IMUNE often carry sufficient information content toidentify organisms, antigens, and epitopes without prior knowledge ofwhich organism or antigens may be important. About 80% of motifs thatIMUNE identified that were sensitive and specific could be associatedwith a B. burgdorferi antigen epitope, by performing degenerate motifsearches within the entire Swissprot/TrEMBL databases using Scanprosite.See Table 2.

TABLE 2Motifs and peptides comprising panel for the diagnosis of Lyme Disease.ID Panel motif Antigen(s); peptide sequence(s)  1 VQQExxxxxP (SEQ ID NO:Flagellin (Fragment); VQQEgaqqqP (SEQ ID NO: 392) 358)  2 QQEGxxxx[YC](SEQ ID NO: 359)  3 QEG[IV]Q (SEQ ID NO: 360)Flagellar filament 41 kDa core protein (Flagellin);QEGVQ (SEQ ID NO: 393)  4 G[IV]QxEG (SEQ ID NO: 361)Flagellar filament 41 kDa core protein (Flagellin);GVQqEG (SEQ ID NO: 394)  5 [LI]xxA[ILV]xxRG (SEQ IDFlagellar hook-basal body complex protein FliE; NO: 362)IlkAVveRG (SEQ ID NO: 395)Outer surface protein VlsE; IaaAIvlRG (SEQ ID NO: 396)  6[ATNSD]xxxxAI[LAM]xR (SEQOuter surface protein VlsE; DqiaaAIAlR (SEQ ID NO: ID NO: 363) 397)Flagellar M-ring protein; AkkmrAILvR (SEQ ID NO: 398)Telomere resolvase ResT; AenhkAILfR (SEQ ID NO: 399)  7Ix[LM]xGFxK (SEQ ID NO:Uncharacterized protein; IkLpGFkK (SEQ ID NO: 400) 364)Transglycosylase SLT domain protein; IfLeGFlK (SEQ ID NO: 401)  8LxGM[RQ]K (SEQ ID NO: 365)Uncharacterized protein; LrGMRK (SEQ ID NO: 402)  9[HR]xDxTNxF (SEQ ID NO: 366) 10 [DA]DPTN (SEQ ID NO: 367)Outer surface protein VlsE1; DDPTN (SEQ ID NO: 403) 11[KR]x[DE]xTNxF (SEQ ID NO:Borrelia ORF-A superfamily protein; KtDrTNdF (SEQ ID 368) NO: 404)Outer surface protein VlsE; KdDpTNkF (SEQ ID NO: 405)CdsJ; KtDrTMF (SEQ ID NO: 406) BBD14-like protein (Fragment); KtDkTNdF12 [ET][ML]HFK (SEQ ID NO: PF-32 protein; TLHKF (SEQ ID NO: 407) 369) 13[ML]xxEFHK (SEQ ID NO: 370) 14 Q[TI]EQxxxxxK (SEQ ID NO:Integral outer membrane protein P66; QTEQsststK (SEQ 371) ID NO: 408) 15DxSP[IL]E (SEQ ID NO: 372)Uncharacterized protein; DlSPIE (SEQ ID NO: 409) 16PFx[AP]YxK (SEQ ID NO: 373)Integral outer membrane protein P66; PFsAYiK (SEQ ID NO: 410) 17VxxVFxx[LV]xK (SEQ ID NO: VlsE (Fragment); VkdYFdsLaK (SEQ ID NO: 411)374) 18 KxVDxDR (SEQ ID NO: 375) 19 [DN][AS]A[AG]F (SEQ ID NO:VlsE (Fragment); DAAAF (SEQ ID NO: 412) 376) 20Cx[NA]xKFC (SEQ ID NO: 377) 21 Kx[GRST]AE[YF] (SEQ ID NO:Flagellar basal-body rod protein FlgG (Distal rod 378) protein); KiRAEFPutative lipoprotein; KfRAEF (SEQ ID NO: 413) Na+/H+antiporter family protein; KsSAEF (SEQ ID NO: 414)VlsE (Fragment); KgGAEF (SEQ ID NO: 415) 22 HQV[PA]xxx[DHE] (SEQ IDNO: 379) 23 IPxxV[IF]xxR (SEQ ID NO: 380) 24 Cx[ALT]xWEx[CA] (SEQ IDNO: 381) 25 CxxxCA[IL]xxR (SEQ ID NO: 382) 26 I[IV]Ixx[MT]xK (SEQ ID NO:Lectin; IIIidTsK (SEQ ID NO: 416) 383) CdsC; IIIngMtK (SEQ ID NO: 417)Mlp; IIItnMeK (SEQ ID NO: 418) 27 QG[ITL]x[KN][FY] (SEQ IDDephospho-CoA kinase; QGINY (SEQ ID NO: 419) NO: 384)Phosphomannomutase; QGIcNY (SEQ ID NO: 420) 28 KxxPPxIN (SEQ ID NO: 385)Outer surface protein VlsE1; KetPPaLN (SEQ ID NO: 421) 29G[YF][FY]FxxK (SEQ ID NO:Pts system, iibc component; GFYFifK (SEQ ID NO: 422) 386) 30 DKNVx[IV](SEQ ID NO: 387) Putative lipoprotein; DKNVkI (SEQ ID NO: 423) 31[QE][KR][ND]xSG (SEQ IDOuter surface protein B (OspB); EKNsSG (SEQ ID NO: NO: 388) 424) 32K[RK]PGD (SEQ ID NO: 389)Outer surface protein VlsE; KKPGD (SEQ ID NO: 425) 33EGAxQP (SEQ ID NO: 390)Flagellar filament 41 kDa core protein (Flagellin);EGAqQP (SEQ ID NO: 426) 34 GSPEY (SEQ ID NO: 391)Outer membrane protein; GSPEY (SEQ ID NO: 427)

Example 4 Discovery of Motifs for the Diagnosis of Acute or ActiveToxoplasma Gondii Infection

Toxoplasma gondii is a common infectious parasite with a seroprevalenceof about 20% in the US population. Acute infections can in some casesresult in significant morbidities, for example during pregnancy. Themethod of Example 1 above was applied to a set of 30 sera fromindividuals that were either positive for IgG or IgM antibodies byenzyme immunoassay or immunoblot. A panel of 30 motifs indicated ofAcute Toxoplasma infection is shown in Table 3. The panel is capable ofcorrectly detecting 30 specimens in the discovery set (FIG. 8, FIG. 9).

TABLE 3 Motifs and peptides comprising panel for the diagnosis of acuteToxoplasmosis. ID Panel motif Antigen(s); peptide sequence(s)  1HExE[FY]Q (SEQ ID NO:Apical membrane antigen 1 (TgAMA-1); HEhEFQ (SEQ ID 74) NO: 428)  2LD[MLF]WxE (SEQ ID DNA polymerase, TLD protein, Putative transmembraneNO: 75) protein; LDFWrE (SEQ ID NO: 429, LDFWqE (SEQ ID NO:430), LDMWeE (SEQ ID NO: 431)  3 HCSAC (SEQ ID NO: 76)Putative anaphase promoting complex subunit 11,Palmitoyltransferase, Sulfite exporter TauE/SafE protein;HCSAC (SEQ ID NO: 432)  4 [FY]xGVVN (SEQ ID NO:Dense granule protein 2 (Protein GRA 2) (28 kDa antigen) 77)(GP28.5), Dynein, axonemal, heavy chain 2 family protein;FsGVVN (SEQ ID NO: 433), YpGVVN (SEQ ID NO: 434)  5KxxxGRGxI (SEQ ID NO:NOL1/NOP2/sun family protein; KgshGRGfI (SEQ ID NO: 78) 435)  6GPH[LA]E (SEQ ID NO:Zinc finger (CCCH type) motif-containing protein, Glycogen 79)synthase, Uncharacterized protein; GPHAE (SEQ ID NO: 436)  7PRREP (SEQ ID NO: 80)Dense granule protein 7 (Protein GRA 7) (29 kDa excretorydense granule protein), Putative transmembrane protein, Densegranule protein GRA9; 1,3-beta-glucan synthase componentprotein; PRREP (SEQ ID NO: 437)  8 CNxxxECY (SEQ ID NO: 81)  9KxCQPxxC (SEQ ID NO: 82) 10 PxPD[FH][TS] (SEQ IDDense granule protein 2 (Protein GRA 2) (28 kDa antigen) and NO: 83)SAG-related sequence protein SRS15A; Uncharacterizedprotein; Tetratricopeptide repeat-containing protein;Flagellar/basal body protein, PGAP1 family protein;PvPDFS (SEQ ID NO: 438), PvPDFT (SEQ ID NO: 439),PIPDFT (SEQ ID NO: 440), PlPDFS (SEQ ID NO: 441), PaPDFS (SEQ ID NO: 44211 NxxxExY[AG]xD (SEQ IDO-linked N-acetylglucosamine transferase, Zinc knuckle NO: 84)protein; NaglEvYAeD (SEQ ID NO: 443, NrrrErYGeD (SEQ ID NO: 444 12P[AG]AxxLD (SEQ IDDense granule protein 3 (P30), Uncharacterized protein, NO: 85)GRAM domain-containing protein, Concanavalin A-likelectin/glucanase family protein; PGAvlLD (SEQ ID NO: 445,PAAskLD (SEQ ID NO: 446), PAAesLD (SEQ ID NO: 447),PGAarLD (SEQ ID NO: 448), PGAldLD (SEQ ID NO: 449) 13MPSxSxE (SEQ ID NO:Uncharacterized protein, Toxoplasma gondii family A protein, 86)Putative Tbc domain related protein; MPSwSnE (SEQ ID NO:450), MPStSdE (SEQ ID NO: 451, MPSeStE (SEQ ID NO:452), MPSaSpE (SEQ ID NO: 453) 14 [RK]xYxHR[TS] (SEQ ID Putative 5′-3′exoribonuclease, Glycosyltransferase, Ribosomal NO: 87)protein RPL3; RlYvHRS (SEQ ID NO: 454), RlYrHRT (SEQID NO: 455), KgYfHRT (SEQ ID NO: 456) 15 K[PA]xFxFxK (SEQ IDMicronemal protein 6, GCC2 and GCC3 domain-containing NO: 88)protein; KPpFeFgK (SEQ ID NO: 457), KPgFvFlK (SEQ ID NO: 458) 16DD[CST]xGxR (SEQ ID Dense granule protein 5 (Protein GRA 5) (p21),NO: 89) Uncharacterized protein, RNA pseudouridine synthasesuperfamily protein, AP2 domain transcription factor AP2XI-5;DDSeGaR (SEQ ID NO: 459), DDScGrR (SEQ ID NO: 460),DDSkGdR (SEQ ID NO: 461), DDSsGyR (SEQ ID NO: 462) 17P[ML]xxHxMY (SEQ ID NO: 90) 18 Kx[ASQ][SAT]xRG (SEQDense granule protein 2 (Protein GRA 2) (28 kDa antigen), ID NO: 91)Alpha/beta hydrolase family protein, Putative transmembraneprotein, Radical SAM domain-containing protein, Rhoptry neckprotein RON8; KeAAgRG (SEQ ID NO: 463), KdASlRG (SEQID NO: 464), KgSSgRG (SEQ ID NO: 465), KtSSrRG (SEQ IDNO: 466), KtQTvRG (SEQ ID NO: 467), KrSTlRG (SEQ ID NO: 468) 19[DG]QPEN (SEQ ID NO:Dense granule protein 3 (P30), FHA domain-containing 92)protein, Uncharacterized protein; DQPEN (SEQ ID NO: 469),GQPEN (SEQ ID NO: 470) 20 [KHR]N[QN]DG (SEQ IDCalcium-dependent protein kinase CDPK1, La domain protein, NO: 93)DNA polymerase, SAG-related sequence SRS34A, Surfaceantigen 2(p22); KNNDG (SEQ ID NO: 471), RNNDG (SEQ ID NO: 472) 21Nx[EVS]GExY (SEQ IDEGF family domain-containing protein, Kringle domain- NO: 94)containing protein; NlVGEeY (SEQ ID NO: 473), NdSGEiY (SEQ ID NO: 474)22 EP[VI]TG (SEQ ID NO:Dense granule protein 3 (P30), Corepressor complex CRC230, 95)Cpw-wpc domain-containing protein; EPVTG (SEQ ID NO: 475) 23 HGM[PA][KR](SEQ ID Dense granule protein GRA8, Tetratricopeptide repeat- NO: 96)containing protein; HGMPK (SEQ ID NO: 476), HGMAK (SEQ ID NO: 477) 24[VIT]PWIF (SEQ ID NO:SAG-related sequence SRS57, Putative zinc finger protein; 97)VPWIF (SEQ ID NO: 478) 25 Kx[STN]VxFQ (SEQ IDPutative cell-cycle-control protein (Translation regulation), NO: 98)MaoC family domain-containing protein, Hydrolase, NUDIXfamily protein; KsSVpFQ (SEQ ID NO: 479), KeTVnFQ (SEQ ID NO: 480) 26[VAI]WSGS (SEQ ID NO:Sma protein, Ribosomal protein L9, N-terminal domain- 99)containing protein; VWSGS (SEQ ID NO: 481), IWSGS (SEQ ID NO: 482) 27FS[LIAM]xxWG (SEQ IDPyruvate carboxylase, AP2 domain transcription factor AP2IX- NO: 100)5, Putative transmembrane protein, Putative major facilitatorfamily transporter, Tub family protein; FSLenWG (SEQ ID NO:483), FSMgrWG (SEQ ID NO: 484), FSLvlWG (SEQ ID NO:485), FSLvlWG (SEQ ID NO: 486), FSLtnWG (SEQ ID NO: 487) 28PTN[PQ]G (SEQ ID NO: Uncharacterized protein; PTNQG (SEQ ID NO: 488),101) PTNPG (SEQ ID NO: 489) 29 [RK]Kxx[YW]xHx (SEQPutative type I fatty acid synthase, O-phosphoseryl-tRNA(Sec)ID NO: 102) selenium transferase,NADH/NADH kinase domain-containing protein; RKlhWnHrT (SEQ ID NO: 490),KKyrYrHpT (SEQ ID NO: 491), RKavYqHnT (SEQ ID NO: 492) 30[HRW]xxHPRF (SEQ IDUncharacterized protein, Putative calcium signaling protein NO: 103)kinase RAD53, Glutamate 5-kinase domain-containing protein;RtlHPRF (SEQ ID NO: 493), HfrHPRF (SEQ ID NO: 494),RvaHPRF (SEQ ID NO: 495), WqaHPRF (SEQ ID NO: 496)

Example 5 Discovery of Motifs for the Diagnosis of Taenia SoliumInfection (Cysticercosis)

Cysticercosis cause by the tapeworm Taenia solium, is considered a USneglected parasitic infection is a cause of cerebral parasitosis, andthe single most common cause of epilepsy of unknown etiology. Diagnosiscurrently requires costly imaging studies to determine the presence, andnumber, of cysts present in the brain. A total of 30 samples fromindividuals diagnosed with Cysticercosis, with 1 or more cysts, wereanalyzed to determine their epitope repertoires. The method of Example 4was applied to identify infection specific motifs (Table 4). A panel ofmotifs was capable of identifying Cysticercosis specimens (FIG. 10) withhigh specificity.

TABLE 4 Motifs and peptides comprising panel for thediagnosis of Cysticercosis. ID Panel motif or Peptides  1AxSPN[QEA]; (SEQ ID NO: 226) Huntingtin interacting protein 1;Trypsin-like protein, ArSPN(SEQ ID NO: 265), AgSpNri (SEQ ID NO: 266)  2[RP]xAxSxNx[IFMLV] (SEQ ID NO: 227)  3 PDxGVxP (SEQ ID NO: 869);Putative DSCR5 protein, PDgGVmP (SEQ ID NO: 267)  4 NxxLGL[VT](SEQ ID NO: 228); Protein Wnt, NpkLGLT (SEQ ID NO: 268)  5[YF]x[DE]IxxFF (SEQ ID NO: 229)  6 IxHFFxG (SEQ ID NO: 230)  7[ILM][ILM][RK]H[ED]XQ (SEQ ID NO: 231)  8 [ILM][RK]HExQ (SEQ ID NO: 232) 9 KPxx[IL]xLx[KR] (SEQ ID NO: 233) 10 NxDxxYYxx[WF] (SEQ ID NO: 234) 11GLDGP (SEQ ID NO: 235) 12 RSxHDxxN (SEQ ID NO: 236) 13 FDxFN[IL](SEQ ID NO: 237) 14 TIFxGK (SEQ ID NO: 238) 15R[AV]xS[TQ]H (SEQ ID NO: 239) 16 KWHGxY (SEQ ID NO: 240) 17MPEDK (SEQ ID NO: 241) 18 Exxx[FY]x[AS]D[NT] (SEQ ID NO: 242) 19NQSxxKx[VI] (SEQ ID NO: 243) 20 KxY[NAS]PY (SEQ ID NO: 244) 21[PQ][VL]HPRI (SEQ ID NO: 245) 22 EDGMxxW (SEQ ID NO: 246) 23YASXQE (SEQ ID NO: 247) 24 KQxQ[QK]E (SEQ ID NO: 248) 25 K[AS]VFD[IVM](SEQ ID NO: 249) 26 PN[QE]x[DN]P (SEQ ID NO: 250) 27P[QA]XM[DN]I (SEQ ID NO: 251) 28 [WR]x[RKH][ST]xFD (SEQ ID NO: 252) 29KxEPGxK (SEQ ID NO: 253) 30 DDCLP (SEQ ID NO: 254) 31NXXXXGXHLE (SEQ ID NO: 255) 32 DxxHLEG (SEQ ID NO: 256) 33RPxx[TS]HN (SEQ ID NO: 257) 34 KxHS[IV]Y (SEQ ID NO: 258) 35KxHSx[IV]S (SEQ ID NO: 259) 36 MSGYE (SEQ ID NO: 260) 37YXIWGP (SEQ ID NO: 261) 38 RxxWxMN[RK] (SEQ ID NO: 262) 39QPxxT[FY]E (SEQ ID NO: 263) 40 YGYNQ (SEQ ID NO: 264)

Example 6 Discovery of Motifs for the Diagnosis of Mononucleosis by EBVInfection

Mononucleosis caused by EBV can be difficult to diagnosis anddiscriminate from prior EBV exposure and/or viral reactivation. Twentysamples from individuals with confirmed EBV mononucleosis werecharacterized according to the Method of Example 1. Motifs discovered(Table 5) were capable of identifying all specimens from EBV infectionMono cases, with high specificity (FIG. 11). The absence of a particularmotif (for example the RRPFF epitope of EBNA-1) was helpful as an aid toidentify individuals with prior infections, or with prolonged course ofprimary infection.

TABLE 5 Motifs and peptides comprising panel for thediagnosis of Mononucleosis. IDPanel motif and Antigen(s); peptide sequence(s)  1LFGxx[LM]N (SEQ ID NO: 9);BKRF2 (Envelope glycoprotein L); LFGanLN (SEQ ID NO: 44)  2GELxGQ (SEQ ID NO: 852)  3 EWVxx[YF]D (SEQ ID NO: 10  4P[LM]ALxL (SEQ ID NO: 11  5 KxNExWxV (SEQ ID NO: 12  6P[AG]xRTxK (SEQ ID NO: 13;BFLF1 (Packaging protein UL32 homolog); PGpRTcK (SEQ ID NO: 45)BZLF1 (Viral immediate early antigen); PArRTrK (SEQ ID NO: 46)  7AYTxVN (SEQ ID NO: 14)  8 WN[AS]YxxxN (SEQ ID NO: 15)  9[RKE]xxWxP[LM]Q (SEQ ID NO: 16) 10 [AS]YxSx[SA][YF] (SEQ ID NO: 17) 11ExYxSPS (SEQ ID NO: 18) 12 MNIxDD (SEQ ID NO: 19) 13EH[ANK]FW (SEQ ID NO: 20) 14 VHNAY (SEQ ID NO: 21) 15HG[EA]xLN (SEQ ID NO: 22) 16 [GD]xx[LF]xxP[ML]Q (SEQ ID NO: 23) 17[LVMI]xNAx[TS][FGI] (SEQ ID NO: 24);BPLF2 (Large tegument protein); IaNAgSI (SEQ ID NO: 47) 18PxNSYT (SEQ ID NO: 25) 19 RxxPLAxxL (SEQ ID NO: 26) 20CPKxNxT (SEQ ID NO: 27) 21 Q[PA]H[AM]F (SEQ ID NO: 28) 22 PAxEMxxx[GSP](SEQ ID NO: 29) 23 NID[DE]D (SEQ ID NO: 30) 24 RxQx[VS]D[NA](SEQ ID NO: 31) 25 Wx[DP]PxHL (SEQ ID NO: 32) 26 TWA[FI][FI](SEQ ID NO: 33) 27 EDxGHP (SEQ ID NO: 34) 28[ETA]xxx[YF]xxP[SR]Q (SEQ ID NO: 35) 29 GMxP[RK]Q (SEQ ID NO: 36) 30Wxx[VI]RxxPxQ (SEQ ID NO: 37); EBNA-3B nuclear protein;WaqIRhiPyQ (SEQ ID NO: 48) 31 [NE][AG]Y[SAT]xxW (SEQ ID NO: 38) 32KxI[ST]xYW (SEQ ID NO: 39) 33 YYxYRxxK (SEQ ID NO: 40) 34 KxHExG[FY](SEQ ID NO: 41) 35[MLF]xNPQQ (SEQ ID NO: 853); Major capsid protein (MCP);MrNPQQ (SEQ ID NO: 49) 36 HHFL[VI] (SEQ ID NO: 42) 37[LV]CNAY (SEQ ID NO: 43)

Example 7 Discovery of Motifs for the Diagnosis of Zika Virus Infection

A total of 38 specimens from individuals positive for Zika virusinfection by IgG and/or IgM serology and clinical criteria (e.g. redeyes, fatigue, joint pain, etc) using an enzyme immunoassay wereanalyzed. The method of Example 1 was to identify IgG and IgM motifsspecific to Zika virus infection (Table 6, Table 7) Motif panels werecapable of identifying individuals with Zika virus infections (FIG. 12).Similarly, the method of example 1, with the following modifications wasused to identify IgM motifs indicative of Zika infection. Rather thanusing protein A/G beads, peptide displaying cells complexed with IgMwere separated and enriched from non-binders using a biotinylatedmonoclonal antibody specific for human IgM, followed by cell capture onstreptavidin-conjugated magnetic beads.

TABLE 6 IgG motifs comprising IgG panel for the diagnosis of Zika IDPanel motif  1 VRxxYxQH (SEQ ID NO: 319)  2 CEDxxxHxC (SEQ ID NO: 320) 3 DAEQxxR (SEQ ID NO: 321)  4 WPGIF (SEQ ID NO: 322)  5CCYDXE (SEQ ID NO: 323)  6 LxPDNxT (SEQ ID NO: 324)  7FxWGQxY (SEQ ID NO: 325)  8 KxEGHxxxxA (SEQ ID NO: 326)  9CxxGxCQxK (SEQ ID NO: 327) 10 CCxDxx[DE][DE] (SEQ ID NO: 328) 11RNGxED (SEQ ID NO: 329) 12 [DE]xRxIYxQ (SEQ ID NO: 330) 13WxRCGL (SEQ ID NO: 331) 14 D[ED]xRxxYxxH (SEQ ID NO: 332) 15WCxLx[AV]N (SEQ ID NO: 333) 16 LXTPWI (SEQ ID NO: 334) 17 CWxxxGL[CA](SEQ ID NO: 335) 18 ID[AV]EP (SEQ ID NO: 336) 19HF[NK][VT]xK (SEQ ID NO: 337) 20 QxNHQxK (SEQ ID NO: 338)

TABLE 7 IgM motifs comprising IgM panel for the diagnosis of Zika. IDPanel motif  1 FExKEP (SEQ ID NO: 339)  2 [FYW]DA[VI] (SEQ ID NO: 340) 3 DFDKR (SEQ ID NO: 341)  4 WETC (SEQ ID NO: 342)  5KLDGP (SEQ ID NO: 343)  6 WIYPxK (SEQ ID NO: 344)  7V[HS]DSK (SEQ ID NO: 345)  8 EQCGT (SEQ ID NO: 346)  9[KE][MVIT]PYA (SEQ ID NO: 347) 10 [DE]xxML[RP]W (SEQ ID NO: 348) 11YExLHx[FY] (SEQ ID NO: 349) 12 WY[TSN]xEK (SEQ ID NO: 350) 13[YF]H[DNS]AV (SEQ ID NO: 351) 14 DxTG[VI]P (SEQ ID NO: 352) 15FDxxGEH (SEQ ID NO: 353) 16 QC[AK]xx[HE]C (SEQ ID NO: 354) 17LW[FY]xPxE (SEQ ID NO: 355) 18 C[MI][PA]GxxC (SEQ ID NO: 356) 19Cxxxx[AVS]ADC (SEQ ID NO: 357) 20 TTESxV(SEQ ID NO: 854) 21KDV[GA]E (SEQ ID NO: 855) 22 KPxD[FWM]GxK (SEQ ID NO: 856) 23VxADGT (SEQ ID NO: 857) 24 M[AP][AT]AD (SEQ ID NO: 858) 25 VPxPK[DG](SEQ ID NO: 859) 26 QxKP[TS]D (SEQ ID NO: 860) 27F[TS]xDGF (SEQ ID NO: 861) 28 Wx[RK]VY[VA] (SEQ ID NO: 862) 29[CS]T[TS]Exxx[YF] (SEQ ID NO: 863) 30 YxETC[TI] (SEQ ID NO: 864)

Example 8 Discovery of Motifs for the Diagnosis for HIV Infection

Sera from seven individuals with HIV infection were analyzed asdescribred for Example 1. Motifs specific to HIV infection are as shownin Table 8. A panel of motifs was capable of identifying individualswith HIV (FIG. 13), and discrimiting those with infections from thosewithout infections.

TABLE 8Motifs and peptides comprising panel for the diagnosis of HIV infection.ID Panel motif Antigen(s); peptide sequence(s)  1 CxGLIC (SEQ ID NO: 290Envelope glycoprotein gp160; CSGKLIC (SEQ ID NO: 306)  2 CxxKx[IV]C[IV](SEQ ID NO: Envelope glycoprotein gp160; CSGKLICT 291 (SEQ ID NO: 306) 3 W[GAS]CxGxxxC (SEQ ID NO: Envelope glycoprotein gp160; 292)WGCSGKLIC (SEQ ID NO: 308)  4 [RK]KL[IV]E (SEQ ID NO: 293  5KLIMT (SEQ ID NO: 294)  6 [QE]xxPFRY (SEQ ID NO: 295)  7 CxxKx[IV]C[IV](SEQ ID NO: Envelope glycoprotein gp160; 296) CSGKLICT (SEQ ID NO: 309) 8 [LF]xx[LIV][ND]KW (SEQ ID Envelope glycoprotein gp160; LLALDKWNO: 297) (SEQ ID NO: 310)  9 [AP][GC]GFG (SEQ ID NO: 298Envelope glycoprotein gp160; AVGMG (SEQ ID NO: 311) 10LIx[TS]TY (SEQ ID NO: 299 Envelope glycoprotein gp160; LICTT(SEQ ID NO: 312) 11 [RK]KLxx[MV]Y (SEQ ID NO: 300) 12 GF[GA][AQ][AYV](SEQ ID Envelope glycoprotein gp160; GFGAV NO: 301) (SEQ ID NO: 313) 13GFG[RQ]x[FNY] (SEQ ID NO: 302) 14 [KR]KxIH[VIM] (SEQ ID NO:Envelope glycoprotein gp160; RKgIrI (SEQ 303)ID NO: 314) KKgIaI (SEQ ID NO: 315),RKgIhM (SEQ ID NO: 316), RKsIhM (SEQ ID NO: 317) 15R[IV]PFG (SEQ ID NO: 304) 16 KLIxx(SEQ ID NO: 305)Envelope glycoprotein gp160; KLICTT (SEQ ID NO: 318)

Example 9 Sjogren's Syndrome—Discovery of Diagnostic Motifs and Peptides

Primary Sjogen's Syndrome (SS) is a chronic, highly prevalent autoimmunedisease affecting about 0.3-0.5% of people in the western world. Thehallmark symptoms are dry eyes and mouth, which are a result of T celland autoantibody infiltration of the exocrine glands leading to loss ofsecretory function and, over time, eventual gland destruction. Thegradual destruction of the exocrine glands underscores the importance ofearly diagnosis and treatment to patient quality of life. Theheterogeneity of symptoms, their association with aging and lack ofspecific diagnostic tests all contribute to delayed diagnosis with anaverage time of 4.7 years. Serological testing for autoantibodiesincluding La/SS-B, Ro/SS-A, Anti-nuclear antibodies (ANAs) andrheumatoid factor (RF) are used to aid in SS diagnosis, however, they donot provide sufficient specificity to be used as a stand-alonediagnostic test. Identification of novel SS specific biomarkers is thusan important unmet diagnostic need. The heterogeneity of SS may reflectdifferent subcategories of SS with unique sets of autoantibodies, posingan additional diagnostic challenge. In this Example, we identifiedbiomarkers that are specific to SS and defined their association withspecific disease subpopulations. The tests can be combined into a singlemultiplex assay having greater overall specificity and sensitivity thancurrent tests.

Until recently, no SS classification criteria have been universallyaccepted because of the subjective and non-specific nature of SSdiagnostics. The new criteria, endorsed by the American College ofRheumatology, requires a positive result in 2 out of 3 of the followingobjective tests:

1. Positive serum anti-SSA/Ro and/or anti-SSB/La or (positive rheumatoidfactor (RF) and ANA titer 1:320), requiring 3 separate ELISAs and anindirect immunofluorescence assay (IFA).

2. Labial salivary gland biopsy exhibiting focal lymphocyticsialadenitis (focus score 1 focus/4 mm2)

3. Dry eye as measured by staining on the surface of the eye with ocularstaining score 3.

The need for multiple testing modalities is redundant, costly and laborintensive. Identification of a panel of biomarkers that could identifySS with high sensitivity and specificity as a single serological testcould streamline and expedite SS diagnosis and improve patient outcomes.

In this Example, we identified motifs, patterns and peptides specificfor primary Sjogren's Syndrome (pSS). The experiment procedure is asdescribed in Example 1.

Examples of motifs specific to pSS include KPXFXGXK. Specificity ofindividual motifs (e.g., KPXFXGXK) is also evident in dot plots (FIG.14).

To use the pSS motifs for diagnosis of pSS, one obtains a serum or bloodsample, screens a peptide display library using that sample, determinesthe resulting enriched sequences, and then queries for the enrichment ofdisease specific motifs. If one or more disease specific motif ispresent, then enrichment values for the pSS specific motifs aredetermined, and compared to a reference cutoff value.

Example 10 Discovery of Motifs Indicating Latent Epstein-Barr VirusInfection

Epstein-Barr virus (EBV) is a ubiquitous latent infection in the humanpopulation, with B-cells being the primary host for the virus. Despitebeing ubiquitous active EBV is associated with mononucleosis, andreactivation of latent EBV has been associated with various autoimmunediseases. Furthermore, EBV serology has shown to a risk factor forautoimmune diseases, since negative serology for EBV dramatically lowersthe risk of multiple sclerosis. For these reasons, EBV serology isclinically useful.

To identify diagnostic motifs and epitopes useful for EBV serology, 20samples from samples obtained from individuals with EBV mononucleosiswere analyzed for peptide motifs using the methods described above.Peptide motifs were discovered by pattern clustering (e.g. using IMUNEalgorithm).

Among the top 40 most abundant motifs, motifs corresponding to EBVepitopes were identified by searching the motif against thenon-redundant protein database for all exact matches. Nine EBV motifswere identified that exactly matched a corresponding epitope in an EBVprotein. See Table 9. Multiple motifs were experimentally validated tocorrespond to the indicated epitope within EBV.

To diagnose active infection, one or more of the motifs in Table 9 aresearched within an epitope repertoire from any individual to determineserological status for EBV infection. For each motif an enrichment of3-fold or greater is indicative of infection See FIG. 25. Activeinfection can be ascertained by measuring the enrichment for motifscorresponding to BFRF2, GP42, and BVRF2, which correspond to epitopes inviral capsid antigens (VCA).

TABLE 9Exemplary motifs and peptides for serological detection of latentEBV infection. EBV Motif ID Motif Peptide epitope in EBV proteinEBV.EBNA-1.1 GRRPFF (SEQ ID NO: 269) GRRPFF (SEQ ID NO: 281)EBV.EBNA-1.2 GGGxGAGGG (SEQ ID NO: 270) GGGAGAGGG (SEQ ID NO: 282)EBV.EBNA-1.3 EG[PA]ST[GA]R (SEQ ID NO: 271) EGPSTGPR (SEQ ID NO: 283)EBV.EBNA-1.4 KXXSC[IVL]GC[RK] (SEQ ID NO: KRPSCIGCK (SEQ ID NO: 284)272), SCIGCK (SEQ ID NO: 273), CIGC (SEQ ID NO: 274) EBV.GP42.1VXLPHW (SEQ ID NO: 275), KEVKLPHWTPT (SEQ ID NO: 285)LPHW (SEQ ID NO: 276) EBV.BFRF2 PQDT[GA]PR (SEQ ID NO: 277)PQDTAPR (SEQ ID NO: 286) EBV.EBNA-2.1 GPPWWP (SEQ ID NO: 278)GPPWWP (SEQ ID NO: 287) EBV.BVRF2/BdRF1 QQPTTXGW (SEQ ID NO: 279)QQPTTEGH (SEQ ID NO: 288) EBV.EBNA-2.2 [LMIV]FDXDWYP (SEQ ID NO:LFPDDWYP(SEQ ID NO: 289) 280)

Example 11 Discovery of Motifs Related to Rhinovirus Virus Infection,and Determination of Prior Rhinovirus Infection

Human rhinovirus is a common upper respiratory infection in humans, andis associated with a robust immune response. Recent infections typicallyincrease the titer of Rhinovirus specific antibodies. Thus, by measuringthe titer of antibodies towards Rhinovirus motifs or patterns, one canidentify prior or recent infection with Rhinovirus.

Motifs indicative of Rhinovirus are shown in Table 10, searching epitoperepertoires for rhinovirus patterns, peptides, and motifs identifiesindividuals with a humoral immune response against these epitopes, whichcan provide a measure of whom has been infected, and whether theirinfection was recent (by the magnitude of the enrichment signal).

TABLE 10 Exemplary motifs and peptides for serological detectionof Rhinovirus infection or exposure Motif ID MotifPeptide epitope in protein Rhinovirus.VP1.1 L[EDQ]EV[LIV][IV][DE]K (SEQELEEV[IV]VDK (SEQ ID NO: ID NO: 50), 58) E[VI][VIL][IV][DEN]K (SEQ IDNO: 51), E[VI][VI][VI]XK (SEQ ID NO: 52) Rhinovirus.VP1.2VXPNI (SEQ ID NO: 53), VVPN LNEVLVVVPNI (SEQ ID NO: (SEQ ID NO: 54), 59)LXEVLVVVP (SEQ ID NO: 55) Rhinovirus.VP1.3 GPXHTXKV (SEQ ID NO: 56)GPKHTQKV (SEQ ID NO: 60) RhinovirusA.VP1 EXY[VI]DX[VT]LN (SEQ ID NO:EEYVDQVLN (SEQ ID NO: 57) 61)

Example 12 Discovery of Motifs Related to Cytomegalovirus Infection

Human cytomegalovirus (CMV) is a common infectious herpes virus (HHV-5),often infecting salivary glands. CMV can remain dormant or latent intissues for long periods of time, but can be reactivated by variousstimuli. Infections can be life threatening in immunocompromisedindividuals, for instance when infected with human immunodeficiencyvirus (HIV) or after organ transplantation. CMV has been associated withcancers, diabetes, arterial hypertension, and other diseases. See [41,42]. Given this, there is need to identify those infected with CMV anddetermine whether infected individuals are at higher risk of developingspecific diseases.

Diagnosis of CMV infection can be made by looking for the presence ofanti-CMV antibodies although not all of the protein and peptide antigenepitopes are known. Epitope specific detection of prior CMV infectioncan also be useful, for example, to associate clinical phenotypes andrisks to specific antibody species.

To identify motifs indicative of latent CMV infection, epitoperepertoires were determined using laboratory analysis as described abovefor 40 individuals with Sjogren's syndrome and 40 healthy controls,wherein a subset of each group are positive for CMV infection. Peptidespresent in five or more pSS and five or more healthy control epitoperepertoires were then extracted from the sequence files in order toperform motif discovery via clustering with MEME. Among the resultingmotifs were KXDPDXXW[ST] and KPXLGGK, both of which occur in CMVproteins. See Table 11. These CMV associated motifs can be detected inindividual epitope repertoires to assess CMV serology and exposure.

TABLE 11 Exemplary motifs and peptides for serological detection ofCytomegalovirus infection or exposure. Motif ID MotifPeptide epitope in protein CMV.RL13.1 KXDPDXXW[ST] (SEQ ID NO: 62)KXDPDXXWT (X = variable positions in viral protein)(SEQ ID NO: 64)CMV.Teg.1 KPXLGGK (SEQ ID NO: 63) KPtLGGK (SEQ ID NO: 65)

Example 13 Discovery of Motifs Related to Streptococcus Infection

Streptococcus pyogenes and other Streptococcus species are commonpathogens in humans, and accurate diagnosis can help to identify propertreatments. Antibody titer can increase in response to ongoing or recentinfection. Several motifs were identified by using the methodologydescribed herein in a set of individuals with and without autoimmunedisease, grouping peptides present in >30% of samples, and thenperforming motif discovery. See Table 12. Motifs identified were used tosearch for proteins containing these motifs in the non-redundant proteindatabase using Scanprosite. Three motifs identified primarilyStreptococcus associated antigens, including PspC, Streptolysin O, thelater of which is a known target of the human immune response. Here,however, we have identified the protein site targeted by antibodies, andspecific motifs and peptides useful for the detection of theseantibodies in an epitope repertoire, or serum sample, respectively.

TABLE 12Exemplary motifs and peptides for serological detection of Streptococcusinfection Motif ID Motif Peptide epitope in protein Streptococcus.PspC.1[IV]X[PR]QPEKP (SEQ ID NO: 66) VKPQPEKP (SEQ ID NO: 71) Streptococcus.KXDDMLN (SEQ ID NO: 67), KTDDMLN (SEQ ID NO: 72) Streptolysin O.1KXDXMLN (SEQ ID NO: 68) Streptococcus. LW]XSAEXEEK (SEQ ID NO: 69),LESAEKEEK (SEQ ID NO: Streptolysin O.2 SAEXEXK (SEQ ID NO: 70) 73)

Example 14 Discovery of Motifs Diagnostic of Haemophilus InfluenzaInfection

Haemophilus influenza is a gram positive bacteria that infects humans,and is associated with pneumonia, meningitis, sinusitis, and otherconditions. Determination of infection or of specific serotypes orspecies can help to determine proper antibiotic therapy.

To identify motifs indicative of Haemophilus influenza infection orexposure, the methods provided herein were used to determine epitoperepertoires in 40 individuals with Sjogren's syndrome, and 40 healthycontrols. Peptides present in five or more pSS and five or more healthycontrol epitope repertoires were then extracted from the sequence filesin order to perform motif discovery via clustering with MEME. Clusteringidentified the motif MKEAX[SA]EK (SEQ ID NO: 497)which as an epitopeMKEAASEK (SEQ ID NO: 498) in an poorly characterized protein antigen ofHaemophilus influenza.

Example 15 Discovery of Motifs Diagnostic of Leishmani Infection

Samples from individuals (n=11) with Leishmani infections were analyzedby the methods described herein resulting in the motif panel in Table13. A panel of motifs from Table 13 was capable of identifyingindividuals with Leishmania infections (FIG. 15).

TABLE 13 Motifs indicative of Leishmania infection. Leishmania motifPeptide Hit(s) Putative Antigen R[IV]PFG (SEQ ID RVPFG (SEQ ID NO: 519)Uncharacterized protein. Leishmania NO: 499) panamensis and other spRIPFG (SEQ ID NO: 520) DNA-directed RNA polymerasesubunit Leishmania panamensis RIPFG (SEQ ID NO: 521)DNA-directed RNA polymerase subunit(EC 2.7.7.6). Leishmania braziliensis GGlfRVPFG (SEQ ID NO: 522)1-acyl-sn-glycerol-3- phosphateacyltransferase-like protein,putative Leishmania panamensis KGXATP (SEQ ID KGKATPS (SEQ ID NO: 523)Histone H2A.1. Leishmania infantum NO: 500) KGKATPS (SEQ ID NO: 524)Histone H2A. Leishmania donovani P[ML]xVGP (SEQ IDPL[VSPLR]VGP (SEQ ID NO: Uncharacterized protein. Leishmania NO: 501)525) panamensis and other sp PKxDG[RY] (SEQ ID PKvDGR (SEQ ID NO: 526)Protein kinase, putative (EC NO: 502) 2.7.11.1). Leishmania panamensisPKaDGR (SEQ ID NO: 527) Uncharacterized protein. Leishmania panamensisPKaDGY (SEQ ID NO: 528) Uncharacterized protein. Leishmania panamensisPKeDGR (SEQ ID NO: 529) Hydrophilic acylated surface proteinb. Leishmania infantum peptide has multiple repeatsPKeDGR (SEQ ID NO: 530) K26 protein (Fragment). Leishmania infantumpeptide has multiple repeats KxDGH[ES] (SEQ ID KyDGHS (SEQ ID NO: 531)Uncharacterized protein. Leishmania NO: 503) panamensisKcDGHE (SEQ ID NO: 532) Uncharacterized protein. Leishmania panamensisVQx[FY]Mx[RK] VQhYMhR (SEQ ID NO: 865)Uncharacterized protein. Leishmania (SEQ ID NO: 504)panamensis and other sp VQtFMlR (SEQ ID NO: 533) ″VQiYMaK (SEQ ID NO: 534) ″ VQlFMrR (SEQ ID NO: 535) ″ DRxPx[GA]x[VA]VQsYMlR (SEQ ID NO: 536) ″ (SEQ ID NO: 505) VQlYMdK (SEQ ID NO: 537) ″VQlYMdK (SEQ ID NO: 538) Aquaglyceroporin. Leishmcmia donovaniDXIDX[VL]W (SEQ DdIDlLW (SEQ ID NO: 539) ATP ase domain protein,ID NO: 506) putative. Leishmania panamensis and other sp RQPxG[RQ](SEQ ID RQPcGQ (SEQ ID NO: 540) Mitochondrial chaperone BCS1, NO: 507)putative. Leishmania panamensis RQPqGR (SEQ ID NO: 866)Protein kinase, putative (EC 2.7.11.1). Leishmania panamensisRQPiGR (SEQ ID NO: 541) ENOL protein (EC 4.2.1.11)(Fragment). Leishmania braziliensis PxHGIH (SEQ ID NO: 508)DGDGP (SEQ ID NO: DGDGP (SEQ ID NO: 509)Inositol polyphosphate phosphatase, 509)putative (EC 3.1.3.36). Leishmania panamensis DGDGP (SEQ ID NO: 509)Putative inositol polyphosphate phosphatase (EC 3.1.3.36). Leishmaniabraziliensis DGDGP (SEQ ID NO: 509) Hydrophilic acylated surface proteinb. Leishmania infantum Hxx[NQ]TPx[KR] HptNTPeK (SEQ ID NO: 542)Uncharacterized protein. Leishmania (SEQ ID NO: 510)panamensis and other sp HpvNTPdK (SEQ ID NO: 543) ″HavQTPsK (SEQ ID NO: 544) ″ HtfQTPqR (SEQ ID NO: 545) ″HvnQTPyR (SEQ ID NO: 546) ″ HdgNTPaK (SEQ ID NO: 547)Putative kinesin (EC 3.6.4.4). Leishmania infantum K[SA]xNP(SEQKSaNPE (SEQ ID NO: 548) Uncharacterized protein. Leishmania ID NO: 511)panamensis KSiNPE (SEQ ID NO: 549) RNase III domain-containingprotein. Leishmania panamensis KAsNPH (SEQ ID NO: 550)Histone H2B. Leishmania donovani [EQDN]xLPHE (SEQNaLPHE (SEQ ID NO: 551) Uncharacterized protein. Leishmania ID NO: 512)panamensis DaLPHE (SEQ ID NO: 552) EpLPHE (SEQ ID NO: 553)EmLPHE (SEQ ID NO: 554) 2-oxoglutarate dehydrogenase subunit,putative (EC 1.2.4.2). Leishmania panamensis QpLPHE (SEQ ID NO: 555)GQYG[VIM] (SEQ ID GQYGV (SEQ ID NO: 556)Uncharacterized protein. Leishmania NO: 513) panamensisPR[ML]x[DN]K (SEQ ID NO: 514) FGQ[GQ]xxxD (SEQ ID NO: 515)DD[GRS]xTxK (SEQ ID NO: 516) IxT[FP]DR (SEQ ID NO: 517) KxxNIGxx[FY](SEQ KipNIGdkF (SEQ ID NO: 557) DNA-directed RNA polymerase subunitID NO: 518) beta (EC 2.7.7.6). Leishmania panamensis

Example 16 Discovery of Motifs Diagnostic of Babesia Microti Infection

Babesia infections are one of the most common infections transmitted byblood transfusions. Babesia can be spreak by ticks and is commonly aco-infection in individuals infected with Lyme disease. A total of 30samples with confirmed serology for Babesia infections, were analyzedaccording to the methods of Example 1. Motifs specific to individualswith probable or confirmed Babesia infections are shown in Table 14. Apanel of motifs was capable of identifying individuals with Babesiosis(FIG. 16), and discrimiting those with infections from those withoutinfections.

TABLE 14 Exemplary motifs and peptides for serologicaldetection of Babesia infection ID Panel motif  1[ML]L[AS][TA]xK (SEQ ID NO: 558)  2 [VL]x[AS]xDPxxP (SEQ ID NO: 559)  3[KR]x[IL]x[ST][MLF]N (SEQ ID NO: 560)  4 TG[KR]MxxxxQ (SEQ ID NO: 561) 5 GxPY[STA]xxxx[ML] (SEQ ID NO: 562)  6 WE[EDA]x[PA]I (SEQ ID NO: 563) 7 E[IV]xHxxFxR (SEQ ID NO: 564)  8 Kxx[TS]HRxK (SEQ ID NO: 565)  9TFExGxK (SEQ ID NO: 566) 10 WENx[RA]xxx[FI] (SEQ ID NO: 567) 11[NT][MF]FxxxxWxD (SEQ ID NO: 568) 12[PA][GA][IV][MITV]xxP (SEQ ID NO: 569) 13 KxxRxS[YWH]D (SEQ ID NO: 570)14 EKxxRxx[YF][DN] (SEQ ID NO: 571) 15 DTxTPxE (SEQ ID NO: 572) 16WL[DA]QW (SEQ ID NO: 573) 17 K[EN]xxDxWN (SEQ ID NO: 574) 18[GT]GNGG (SEQ ID NO: 575) 19 G[YFW]dXX[QT]P (SEQ ID NO: 576) 20[IV]GxS[RK]x[CR] (SEQ ID NO: 577) 21 [SAT]TPx[ML]E (SEQ ID NO: 578) 22S[DQ]WxWE (SEQ ID NO: 579) 23 DxxY[IT]xx[HF]K (SEQ ID NO: 580) 24K[YF]xxxL[IVT]K (SEQ ID NO: 581) 25 P[VI]xYMQ (SEQ ID NO: 582) 26WPTGxxx[SN] (SEQ ID NO: 583) 27 Kx[IM][VN]xWA (SEQ ID NO: 584) 28W[AP]TG[KR] (SEQ ID NO: 585)

Example 17 Discovery of Motifs Diagnostic of Ehrlichia Infection

A total of 30 specimens with positive IgG or IgM serology for Ehrlichiainfection were analyzed according to the method of Example 1. Motifsspecific to Ehrlichia infection are shown in Table 15. A panel of motifswas capable of identifying individuals with Ehrlichiosis (FIG. 17), anddiscrimiting those with infections from those without infections.

TABLE 15 Exemplary motifs and peptides for serologicaldetection of Erhlichia infection ID Panel motif  1 YxxL[IV]xP[KR](SEQ ID NO: 586)  2 [SA]N[ML]FY (SEQ ID NO: 587)  3 WDGSx[IV](SEQ ID NO: 588)  4 PxxL[IV]KP (SEQ ID NO: 589)  5KxDWDG (SEQ ID NO: 590)  6 RxxxxKxD[HY]D (SEQ ID NO: 591)  7VDVMGN (SEQ ID NO: 592)  8 Ex[NQ][QN]xFY (SEQ ID NO: 593)  9Vx[TS][TS]N (SEQ ID NO: 594) 10 KLHDP (SEQ ID NO: 595) 11 KxDxDT[GN](SEQ ID NO: 596) 12 Y[HA]GWx[SAE] (SEQ ID NO: 597) 13 NPEH[DTE](SEQ ID NO: 598) 14 NPAxQ[HR] (SEQ ID NO: 599) 15 [KR]MNKxx[TP](SEQ ID NO: 600) 16 DWxxx[FY][VK]K (SEQ ID NO: 601) 17GVN[APTS]xK (SEQ ID NO: 602) 18 [IV]x[PR]EGxK (SEQ ID NO: 603) 19RVF[ST][MA] (SEQ ID NO: 604) 20 NxRxx[VI]W[YF] (SEQ ID NO: 605) 21Yxx[MTL]xYNA (SEQ ID NO: 606) 22 Kx[VI]x[ND][IV]W (SEQ ID NO: 607) 23[ED][YF]Q[LQ]H (SEQ ID NO: 608) 24 FGxPSI (SEQ ID NO: 609) 25QLVGxxK (SEQ ID NO: 610) 26 YxxL[IV]xP[KR] (SEQ ID NO: 611)

Example 18 Discovery of Motifs Diagnostic of Anaplasma Infection

A total of 30 specimens with positive IgG serology for Anaplasmaphagocytophilium were analyzed according to the method of Example 1.Motifs specific to Anaplasma infection are shown in Table 16. A panel ofmotifs was capable of identifying individuals with Anaplasmosis (FIG.18), and discrimiting those with infections from those withoutinfections.

TABLE 16 Exemplary motifs and peptides for serologicaldetection of Anaplasma infection. ID Panel motif  1W[YK]Wx[PA]K (SEQ ID NO: 612)  2 KexH[NK]F (SEQ ID NO: 613)  3QxxxWPYxK (SEQ ID NO: 614)  4 YxFDxNxR (SEQ ID NO: 615)  5FxWN[VI]P (SEQ ID NO: 616)  6 [FW][LM]EXAH (SEQ ID NO: 617)  7DF[LI]xAT (SEQ ID NO: 618)  8 KxMSxFV (SEQ ID NO: 619)  9W[YK]Wx[PA]K (SEQ ID NO: 620) 10 KxExH[NK]F (SEQ ID NO: 621) 11QxxxWPYxK (SEQ ID NO: 622) 12 WPT[SF]T (SEQ ID NO: 623) 13WP[TA]GR (SEQ ID NO: 624) 14 KNWPx[GF] (SEQ ID NO: 625) 15KxxP[LI]FA (SEQ ID NO: 626) 16 WPxGQV (SEQ ID NO: 627) 17[VI][LR]KDF (SEQ ID NO: 628) 18 WPT[SF]T (SEQ ID NO: 629) 19Kx[IM][VN]xWA (SEQ ID NO: 630) 20 [YW]TxEPF (SEQ ID NO: 631) 21[AM][PTS]WExF (SEQ ID NO: 632) 22 R[PT][RTK]F[NS] (SEQ ID NO: 633) 23VY[SA]HW (SEQ ID NO: 634) 24 [WF]xxKPxWxxM (SEQ ID NO: 635) 25KGx[SA]HxF (SEQ ID NO: 636) 26 KGxVxF[AS] (SEQ ID NO: 637) 27[IV]xHxTID (SEQ ID NO: 638) 28 MLSXXVN (SEQ ID NO: 639) 29KxYSxxVR (SEQ ID NO: 640) 30 Kx[VK]VNP (SEQ ID NO: 641)

Example 19 Discovery of Motifs for the Diagnosis of Toxocara CanisInfection

Toxocara canis is a common parasitic infection, present in 5-20% ofindividuals in the United states. Diagnosis is dependent upon the use ofserology to detect antibodies present in blood or other body fluids. Themethods of Example 1 were used to develope a panel of motifs (Table 17),which correctly identified individuals with Toxocara canis infections(FIG. 19).

TABLE 17Exemplary motifs and peptides for serological detection of Toxocara canisinfection. ID Panel motif Antigen(s); peptide sequence(s)  1[RKH]EPGD (SEQ ID NO: 642) Putative ubiquitin-conjugating enzyme E2 7,Alpha/beta hydrolase domain-containing protein 14A,Multidrug resistance protein pgp-1, Filamin-A; HEPGD (SEQ ID NO: 680), REPGD (SEQ ID NO:681), KEPGD (SEQ ID NO: 682), REPGD (SEQ ID NO: 683)  2CxxIxNExC (SEQ ID NO: 643)Uncharacterized protein; CkkIvNEtC (SEQ ID NO: 684)  3ESR[SN]I (SEQ ID NO: 644)Disintegrin and metalloproteinase domain-containingprotein 12, 5-formyltetrahydrofolate cyclo-ligase,Putative neurobeachin-like protein, Putative glycogen [starch]synthase; ESRSI (SEQ ID NO: 685), ESRNI (SEQ ID NO: 686)  4HPDx[QN]L (SEQ ID NO: 645)Acetylcholinesterase 1, Sex comb on midleg-likeprotein 2, Cysteine string protein, Transport and Golgiorganization 2-like protein, Secreted frizzled-relatedprotein 5; HPDvNL (SEQ ID NO: 687), HPDgNL (SEQID NO: 688), HPDkNL (SEQ ID NO: 689),HPDeQL (SEQ ID NO: 690), HPDtQL (SEQ ID NO: 691)  5 RYxH[FY][ED](SEQ ID NO: Uncharacterized protein, G2/M phase-specific E3 646)ubiquitin-protein ligase, Sorting nexin-33; RYcHFD(SEQ ID NO: 692), RYyHYD (SEQ ID NO: 693), RYkHFD (SEQ ID NO: 694)  6F[AS]xRQxP (SEQ ID NO: 647)Uncharacterized protein; Methyltransferase-like protein13, Choline transporter-like protein 1, WD repeat-containing protein 46; FSfRQqP (SEQ ID NO: 695),FAhRQqP (SEQ ID NO: 696), FAhRQrP (SEQ ID NO:697), FAtRQgP (SEQ ID NO: 698)  7 QD[AP]RN (SEQ ID NO: 648)Voltage-dependent T-type calcium channel subunitalpha-1H; QDPRN (SEQ ID NO: 699)  8 Lxx[ILM]NQQ (SEQ ID NO: 649)Uncharacterized protein, Putative U5 small nuclearribonucleoprotein helicase, Cullin-5, Signal recognitionparticle 54 kDa protein, Soluble guanylate cyclase gcy-36; LlqLNQQ (SEQ ID NO: 700), LslMNQQ (SEQ IDNO: 701), LfwINQQ (SEQ ID NO: 702), LqkLNQQ(SEQ ID NO: 703), LilLNQQ (SEQ ID NO: 704)  9 [VA]xDGA[WF] (SEQ ID NO:Disintegrin and metalloproteinase domain-containing 650)protein 12, Chondroadherin-like protein, Eukaryotictranslation initiation factor 4E transporter, Zinc fingerA20 and AN1 domain-containing stress-associatedprotein 9, Ras-related protein Rab-21; ApDGAF (SEQID NO: 705), VqDGAF (SEQ ID NO: 706), AgDGAF(SEQ ID NO: 707), AcDGAF (SEQ ID NO: 708), AiDGAF (SEQ ID NO: 709) 10CxLPE[MTS] (SEQ ID NO: 651)Leucine-rich repeat-containing protein 57, Odorantresponse abnormal protein 4, Transforming protein v-Fos/v-Fox, Choline kinase alpha, Neprilysin-2,Kynurenine formamidase; CsLPES (SEQ ID NO: 710),CpLPET (SEQ ID NO: 711), CvLPES (SEQ ID NO:712), CrLPET (SEQ ID NO: 713), CpLPET (SEQ IDNO: 714), CdLPET (SEQ ID NO: 715) 11 FxxMQ[THS]K (SEQ ID NO: 652)2-acylglycerol O-acyltransferase 1, Melanoma-associated antigen G1; FkkMQSK (SEQ ID NO: 716),FlfMQHK (SEQ ID NO: 717) 12 GH[GAS]xLR (SEQ ID NO: 653)Hemicentin-2, PX domain-containing protein kinase-like protein, Putative UDP-glucuronosyltransferaseugt-47, Zinc finger and BTB domain-containingprotein 16; GHStLR (SEQ ID NO: 718), GHSaLR (SEQID NO: 719), GHGtLR (SEQ ID NO: 720),GHGrLR (SEQ ID NO: 721), GHGfLR (SEQ ID NO: 722) 13 Wxx[DE]YxxL[VE](SEQ ID NO: Guanylate cyclase receptor-type gcy-1; WqiDYtsLV 654)(SEQ ID NO: 723) 14 F[HND][YF]PR (SEQ ID NO:Nuclear hormone receptor family member nhr-6, 655)Laminin-like protein epi-1, Striatin-interacting protein2, ATP-dependent RNA helicase cgh-1, Metaltolerance protein 4, IST1-like protein, FERM domain-containing protein 4A; FDFPR (SEQ ID NO: 724),FDYPR (SEQ ID NO: 725), FNYPR (SEQ ID NO: 726) 15PE[FY]TS (SEQ ID NO: 656)Lysine-tRNA ligase, Sodium bicarbonate transporter-like protein 11; PEFTS (SEQ ID NO: 727) 16 CDxPSxxxC (SEQ ID NO: 657)Tripartite motif-containing protein 2; CDaP StrsC 17[FY]xxNGHxF (SEQ ID NO: 658)Protein kinase C-binding protein NELL1, Proteinkinase C; YyqNGHeF (SEQ ID NO: 728), YhvNGHrF (SEQ ID NO: 729) 18YxICxExxC (SEQ ID NO: 659) 19 DCMGxxC (SEQ ID NO: 660)Dynein heavy chain-like protein; DCMGtfC (SEQ ID NO: 867) 20[ML]xTGLx[DE] (SEQ ID NO:TBC1 domain family member 9B, Synaptobrevin-like 661)protein YKT6, Acyl-CoA dehydrogenase familymember 10, Cohesin subunit SA-1, Geranylgeranyltransferase type-1 subunit beta, Methyltransferase-likeprotein 13; LiTGLpD (SEQ ID NO: 730),MyTGLpE (SEQ ID NO: 731), LwTGLeE (SEQ IDNO: 732), LlTGLaD (SEQ ID NO: 733),LlTGLlD (SEQ ID NO: 734), MdTGLvD (SEQ ID NO: 735) 21MxLGYY (SEQ ID NO: 662) Latrophilin-3; MrLGYY (SEQ ID NO: 736) 22MP[LT]Gx[YH] (SEQ ID NO: Epoxide hydrolase 1; MPTGgH (SEQ ID NO: 737)663) 23 [FL]QTGx[IL] (SEQ ID NO:Protein FAM43A, Protein NDNF, 4-coumarate--CoA 664)ligase 1; LQTGtL (SEQ ID NO: 738), LQTGkL (SEQID NO: 739), FQTGdI (SEQ ID NO: 740) 24 Kx[TS]CPC (SEQ ID NO: 665) 25CKD[TSD]C (SEQ ID NO: 666) 26 CG[VA]F[EQ] (SEQ ID NO: 667)C-type lectin Tc-ctl-4, Collectin-12, Thyroid adenoma-associated-like protein; CGAFE (SEQ ID NO: 741), CGVFQ (SEQ ID NO: 742)27 SNx[IVAE]Axx[IML] (SEQ IDE3 ubiquitin-protein ligase UBR5, Hyaluronidase-1, NO: 668)DNA repair protein RAD2, Seipin, Ectopic P granulesprotein 5, Serpentine receptor class alpha/beta-14;SNrVAsfL (SEQ ID NO: 743), SNkAArqM (SEQ IDNO: 744), SNsAAvdL (SEQ ID NO: 745),SNdVAkiI (SEQ ID NO: 746), SNaVAqvL (SEQ IDNO: 747), SNnVAfeI (SEQ ID NO: 748) 28 PTxLxHx[KR] (SEQ ID NO: 669)Putative thiosulfate sulfurtransferase, Sodium/hydrogenexchanger, F-box/WD repeat-containing protein 5;PTgLdHhR (SEQ ID NO: 749), PTyLiHeR (SEQ ID NO: 750) 29WPVNN (SEQ ID NO: 670) 30 [VIA]CN[GD]xxxxC (SEQ ID NO:Anoctamin-5, Laminin subunit alpha-2, Laminin-like 671)protein. epi-1, Vacuolar protein sorting-associatedprotein 45; ICNDssrrC (SEQ ID NO: 751),ACNGhsitC (SEQ ID NO: 752), VCNGhadtC (SEQ IDNO: 753), ACNGehsqC (SEQ ID NO: 754) 31 [KR]NP[YS]L (SEQ ID NO: 672)ATP synthase lipid-binding protein, mitochondrial,Transmembrane cell adhesion receptor mua-3, Putative39S ribosomal protein L49, mitochondrial, Nucleardistribution protein nudE-like 1, Putative serineprotease, Cytosolic non-specific dipeptidase;RNPSL (SEQ ID NO: 755), KNPSL (SEQ ID NO: 756) 32 CXXXPMXVXC (SEQ ID NO:673) 33 G[LM][KQT]FxxD (SEQ ID NO:Meiotic recombination protein DMC1/LIM15-like 674)protein, Serine/threonine-protein kinase WNK1, 40Sribosomal protein 53a, Epidermal growth factorreceptor kinase substrate 8, WD repeat-containingprotein 82, Dipeptidyl peptidase family member 6;GLTFqaD (SEQ ID NO: 757), GLQFafD (SEQ ID NO:758), GMKFtrD (SEQ ID NO: 759), GLQFpsD (SEQID NO: 760), GLKFspD (SEQ ID NO: 761), GLTFtpD (SEQ ID NO: 762) 34[IA]PMx[PAK]N (SEQ ID NO:Phosphopantothenoylcysteine decarboxylase, Protein 675)kinase C, Achaete-scute-like protein 5, Small nuclearribonucleoprotein Sm D3; APMdAN (SEQ ID NO:763), IPMdPN (SEQ ID NO: 764), APMpKN (SEQ IDNO: 765), APMfKN (SEQ ID NO: 766) 35 WxWCx[HT]xxxC (SEQ ID NO: 676) 36FxxM[QMHE][TH]K (SEQ ID NO:Melanoma-associated antigen G1, Uncharacterized 677)protein; FlfMQHK (SEQ ID NO: 767), FfdMETK (SEQID NO: 768), FeeMQTK (SEQ ID NO: 769) 37 KxEx[VI]xWR (SEQ ID NO: 678)Uncharacterized protein; KrEiVfWR (SEQ ID NO: 868) 38CH[NT]GxC (SEQ ID NO: 679) Transcriptional repressor NF-X1-like protein;CHTGpC (SEQ ID NO: 770)

Example 20 Agents for the Removal or Depletion of Commonly OccurringAntibodies from a Sample

Circulating antibody biomarkers have multiple applications in medicine,including without limitation the diagnosis and monitoring of infections,autoimmunity and cancer, as well as therapeutic and vaccine developmentand validation. One of the greatest challenges in the unbiased discoveryof disease-specific antibody biomarkers is the sorting and filtering ofthe vast number (10⁵-10⁸) of unique antibody specificities in anyindividual repertoire to identify those shared antibody specificitiesassociated with disease. Although each person's antibody repertoire isunique, a large proportion of antibodies react with common environmentalantigens to which people are routinely exposed. Many of these antibodiesmap to one or a few common epitopes on a given antigen. Removal of thesecommon antibodies from serum prior to biomarker discovery could, inprinciple, substantially narrow the individual antibody repertoire“noise” allowing for more sensitive and streamlined discovery of diseasespecific antibodies.

The purpose of this Example is to create a library of peptides that bindto common shared antibody specificities that can be used to remove theseantibodies from serum to facilitate improved biomarker discovery. ForDisplay-seq analysis, this “Depletion reagent” could be used in additionto or in lieu of standard E. coli cell depletion as described in theExamples above. The resulting depleted serum would contain a smaller,more patient specific subset of each person's antibody repertoire andwould eliminate noise from high titer, non-disease specific antibodies.

Experimental Design Summary

Serum was pooled (3 samples/pool) and used to iteratively sort the X12peptide library for 14 rounds of affinity selection by a combination ofMagnetic activated cell sorting (MACS) and Fluorescence activated cellsorting (FACS). To establish whether this process would converge on asimilar set of peptides, two tracks were performed in parallel, eachcontaining a unique set of sera (no overlap). Sorting was stopped whenthe libraries demonstrated a similar reactivity to serum pools used forscreening and naïve pools not used for screening.

Serum Sample Preparation

Each pool was comprised of serum samples from a combination of healthy,Sjogren's syndrome, Myasthenia Gravis and Systemic Lupus Erythematosasera. Each pool was diluted to a final pooled serum concentration of1:100 (1:300 individual serum concentration). The pooling strategy andserum dilution were chosen to favor common specificities that would beat a higher titer and/or present in more than one patient in a givenpool. Serum pools were depleted of E. coli binding antibodies byincubation with E. coli expressing scaffold only (standard E. colidepletion protocol, see Example 1).

X12 Library Screen

E. coli depleted serum pools were used to screen a naïve bacterialdisplay peptide library with twelve random positions (X12 naïve library)to enrich for peptide mimitopes representing common, abundant antibodyspecificities. A total of fourteen rounds of screening were performedusing a combination of MACS and FACS. The final four rounds of sortingwere performed using pools composed exclusively of serum from healthydonors to reduce the likelihood of selecting for a disease-specificantibody specificity that may have been enriched in an earlier sort witha disease-containing serum pool.

The X12 library (diversity 7×10⁹) was grown, induced to express peptidesand sorted by MACS and FACS using standard protocols. A summary of thesteps is given below:

Library Propagation step: The X12 library was grown to OD 0.4-0.6 in LBmedium with chloramphenicol, and peptide expression was induce with0.02% arabinose for 1 hour.

Library clearing step: Peptide libraries were first cleared of protein Aand protein G binders by incubating the induced library with magneticbeads coated with protein A and protein G. Magnetic separation capturesthe beads along with any cells that are bound to the protein coating thebeads. The unbound fraction is collected for screening for serumantibody binders.

MACS Enrichment

Antibody binding step: A pool of (E. coli depleted) serum diluted in PBSwas incubated with Protein A and G cleared cells expressing the peptidelibrary. Antibodies from serum that bound to expressed peptides on thecells were harvested using centrifugation followed by washing with PBSTto eliminate non-specific interactions.

Library enrichment step: Washed cells were then incubated with magneticbeads coated with protein A and protein G to capture antibodies from theserum along with the cells expressing peptides the antibodies areinteracting with. The beads were washed 5 times with PBST whilemagnetized to remove cells captured non-specifically.

Growth step: The enriched library (bound to washed beads) wasresuspended in LB medium and grown overnight to amplify the library.

Repeat MACS enrichment: MACS enrichment was repeated (×3) with a newserum pool until the estimated library diversity was in the ˜10⁵ rangeand could be sorted using FACS.

FACS Enrichment and Analysis

Antibody binding step: A different serum pool was used for eachsubsequent round of enrichment. A pellet of induced cells from theprevious enrichment round representing 10× the predicted librarydiversity was incubated with serum, the sample was centrifuged, unboundantibodies in the supernatant were removed and the pellet was washed toremove non-specific antibody binders.

Library enrichment step: The cell pellet was resuspended in PBScontaining a secondary anti-human IgG antibody labeled withPhycoerythrin and incubated to allow for binding to serumantibody-peptide complexes. Cells were centrifuged, the supernatant wasremoved and the pellet was resuspended in PBS. Cells with boundsecondary antibody above background fluorescence were sorted. A minimumof 10 fold over the predicted library diversity was sorted for eachround for enrichment steps.

Growth step: The enriched library was resuspended in LB medium and thecaptured cells were grown overnight to amplify the library.

Next Generation Sequencing to Identify Peptide Sequences

To identify the peptides that were enriched in each of the libraries,the plasmids were purified from the final round of sorting of eachlibrary and the amplicons prepared for next-generation sequencing usingestablished Illumina protocols. Briefly, the peptide-encoding region ofthe plasmid DNA was amplified and barcoded using two rounds of PCR.Samples were pooled and run on the Illumina NextSeq Platform. Paralleltracks were run with separate bar codes to enable a comparison of totalsequence diversity in each library and evaluate the motif overlap anddetermine whether both tracks converged on a set of similar motifs.

Depletion Library Analysis

The Depletion Screen Enriched for Common Antibody Specificities

To evaluate whether the screening process was effective and establish anendpoint for the screen, enriched library pools were analyzed forreactivity to naïve serum pools at various points throughout thescreening process. Results are the combined data from both tracks. Thefinal libraries showed >75% binding to ten naïve serum pools indicatingthat the libraries are highly enriched for cross-reactive antibodymimitopes.

NGS Results and Motif Analysis

The Screening Process Identified a Highly Overlapping Set of Motifs fromTwo Independent Screens

Each library track contained a similar number of unique sequences (Track1—49,413 Track 2—51,956). To identify enriched motifs and determinewhether the screening process selected for a similar set antibodyspecificities, peptide sequences were compared between the two librariesusing IMUNE software, and separated into those that were present in bothtracks versus those that were unique to one or the other track. The twotracks shared a total of 1605 full peptides, representing ˜3% of theindividual library diversities. Next, the peptide sequences that werepresent in both libraries versus those unique to Track 1 or Track 2 wereranked according to the number of times they appeared in the NGS data.Motifs were generated from the top 5000 peptides from Track 1 only,Track 2 only or both Tracks using MEME. The MEME motifs discovered fromeach of these analyses are in data room/Depletion Reagent/MEME. A totalof 81 unique motifs were identified from the three MEME analyses. SeeTable 18.

The degree of motif overlap between the two libraries was quantifiedusing the Human Antibody Specificity Repertoire Database (HASRD). TheNGS sequence data for the libraries was uploaded and samples werequeried with all identified MEME motifs. Of the 81 motifs identified,91% were present in both libraries indicating a high degree of motifoverlap between the two Tracks. Thus, even though the librariesprimarily contained unique peptides, the two separate screens bothselected for a common set of highly cross-reactive antibodyspecificities. The peptide and motif overlap is summarized in Table 19.

TABLE 18 Top Depletion Reagent Motifs Identified by MEME [VI]PEFXG[SA](SEQ ID NO: Y[IVM]DXX[LM]N (SEQ ID DDKGK (SEQ ID NO: 773) 771) NO: 772)KXPEEP (SEQ ID NO: 774) [LM]XLPDK (SEQ ID NO: 775)[IVY]DXXGN (SEQ ID NO: 776) E[VI][VI][VI]DK (SEQ ID NO:[ML][WY]WMDK (SEQ ID NO: NPVE (SEQ ID NO: 779) 777) 778)CMNXXC (SEQ ID NO: 780) [RK]DX[ML]GR (SEQ ID NO: [IV]XXPXY[DE]K (SEQ ID781) NO: 782) PXG[TV]LXK (SEQ ID NO: [VI]XXQPXKP (SEQ ID NO: DTXP[RK](SEQ ID NO: 785) 783) 784) CXXPWVXXEXC (SEQ ID NO:W[WF]X[QIV]PDK (SEQ ID PPWW (SEQ ID NO: 788) 786) NO: 787)[LI]N[KR]P (SEQ ID NO: 789) P[IL]XNX[HP]XW (SEQ ID NO:[FY]XHXX[LIM]N (SEQ ID 790) NO: 791) [PW]FXXM[DN]KP (SEQ IDK[FYW]THP (SEQ ID NO: 793) YXPTXX[WY] (SEQ ID NO: NO: 792) 794)PXAIXD[LMI][LVI] (SEQ ID YXDXX[LM]N (SEQ ID NO: C[WN]X[WR]XC (SEQ ID NO:NO: 795) 796) 797) KXDPDXXW (SEQ ID NO: 798) [RK]C[YF][LIVM]C[ED] (SEQWCWK[DE] (SEQ ID NO: 800) ID NO: 799) [VI]X[LFM]PHW (SEQ ID NO:PXL[ST]XXE (SEQ ID NO: PX[IV]XEXXM[FW] (SEQ ID 801) 8020) NO: 803)DPYQXX[WF] (SEQ ID NO: [VI]PXLXXXE (SEQ ID NO: YNPF (SEQ ID NO: 806)804) 805) PVXF[ND]K (SEQ ID NO: 807) PXXFYN (SEQ ID NO: 808)PYXXYQ (SEQ ID NO: 809) [RH][RK][PW]FF (SEQ ID NO:KXRPXW (SEQ ID NO: 811) CXNWXXXC (SEQ ID NO: 810) 812)C[IWML]NXXDC (SEQ ID NO: KXDXMXN (SEQ ID NO: 814) WXKXXGXW (SEQ ID NO:813) 815) PXDT[SA]PR (SEQ ID NO: 816) PPT[YFW][LM]G (SEQ ID NO:[YF]X[YF]XXFN (SEQ ID NO: 817) 818) [LM]XXGWNXKP (SEQ ID NO:KX[IVF]PXYL (SEQ ID NO: YXX[IV]PW[ML] (SEQ ID NO: 819) 820) 821)GAGGG (SEQ ID NO: 822) CX[ND]XPXXC (SEQ ID NO: HXP[ML][FMY]Y (SEQ ID NO:823) 824) PDDI[SG]K (SEQ ID NO: 825) FPXXWYP (SEQ ID NO: 826)DMNXH (SEQ ID NO: 827) [KR][LMI]VXQS[SN] (SEQ ID WDXXDG (SEQ ID NO: 829)PXXNXX[LI][TS] SEQ ID NO: NO: 828) 830) [VMI]VPEXK (SEQ ID NO:PX[VI][FYW]XNXP (SEQ ID SGP[KR][HY] (SEQ ID NO: 831) NO: 832) 833)KXXFPQ (SEQ ID NO: 834) PDXXWXK (SEQ ID NO: 835) QP[LM][FM]Y (SEQ ID NO:836) [YF]XCT[FYM]MC (SEQ ID [FW]XPXX[LMI][QN][RK] (SEQ [IV]CWSX[PC](SEQ ID NO: NO: 837) ID NO: 838) 839) PDXP[VI]S (SEQ ID NO: 840)P[LI]XGXPW (SEQ ID NO: 841) ELPRX[YML] (SEQ ID NO: 842) PESHN[DW](SEQ ID NO: 843) YXXTLX[YW] (SEQ ID NO: [VI]XWNXP (SEQ ID NO: 845) 844)G[WYF]DXXD[GP] (SEQ ID KX[TSN]HPG[ED] (SEQ ID NO: MMXHI (SEQ ID NO: 848)NO: 846) 847) KPXLGX[KR] (SEQ ID NO: N[SD]SMN (SEQ ID NO: 850)WXXWF (SEQ ID NO: 851) 849)

TABLE 19 Full peptides versus motif overlap in Depletion reagent tracksTrack I Track II NGS Unique sequences 49413 51956 # unique peptidescommon to both libraries 1605 (~3%) # of motifs common to both libraries74/81 (91%)

The Depletion Library Enriched for Motifs that are Well Represented inthe General Population

To establish the cross-reactivity of the Depletion reagent motifs in thegeneral population, 358 serum samples (including healthy, Sjogren'ssyndrome, Systemic Lupus Erythmatosus, Myasthenia Gravis, Celiac andChagas disease sera) that had been screened using Display Seq werequeried for motif enrichment in HASRD. Display seq recovers between˜0.5-3×10⁶ unique antibody binding peptides per serum samplerepresenting the diversity of each subject's antibody repertoire. Thesesequences were uploaded to HASRD and the percentage of subjects thatshowed enrichment for each motif was tabulated. “Enrichment” was definedas an E value of ≥3 where an E=1 is background (the number of uniquepeptides observed for a given motifs is equal to what would be expectedby random chance). The percentage of patient serum samples that showed≥3-fold enrichment for each of the 81 motifs queried is shown in FIG.20. Serum cross-reactivity ranged from 8-98% with an average of 48% ofsubjects showing motif enrichment. Ninety four percent of the motifswere enriched in at least 20% of the samples queried and enrichment wasevenly distributed between healthy and disease sera.

Depletion Reagent Validation

The Depletion Reagent Effectively Removes Common Antibody Specificitiesfrom Serum

In order to be a useful tool in biomarker discovery, the DepletionReagent should effectively remove common antibodies from serum, therebyenhancing biomarker discovery. To test the ability of the library toeffectively deplete sera of common antibody specificities, three healthyserum samples were depleted using either standard conditions with E.coli expressing eCPX scaffold alone, or with the Depletion reagentconsisting of both Track 1 and Track 2 pooled libraries, according toestablished protocols. Depleted serum was then used to screen the X12bacterial display library at a final serum dilution of 1:25 by theDisplay Seq method. Samples were processed for NGS as describedpreviously and the unique peptide sequences returned for each samplewere uploaded to HASRD and queried with motifs known to be present inthe Depletion Reagent. The enrichment values for several common motifsfrom serum depleted using standard conditions or with the Depletionreagent are shown in FIG. 21. Motifs spanned a large range of enrichmentvalues (˜6 to 400 fold enrichment). Regardless of the level ofenrichment, the Depletion reagent effectively removed antibodies fromthe serum, resulting in reduction in enrichment to or near backgroundlevels.

The ability of the Depletion Reagent to remove common antibodies wasfurther quantified by calculating the percent decrease in motifenrichment after treatment with the Depletion reagent. See FIG. 22. Inthree separate patients, the average enrichment decreased by ˜80-90%.

To understand the effect of the Depletion reagent on reducing thediversity of the antibody repertoire in depleted serum, we compared thereactivity of five serum samples that had been depleted using standardconditions or with the Depletion reagent to the naïve X12 library. Thedepletion reagent reduced the reactivity by ˜5-10-fold, indicating thata significant fraction of antibodies are removed. See FIG. 23.

Removal of Common Antibody Specificities by the Depletion ReagentImproves Detection of Other Antibody Specificities

We wanted to determine whether the Depletion reagent also enhances theability to detect the remaining antibody specificities and/or allows forcapture of a wider diversity of an individuals' antibody repertoire. Toask this question, we queried the serum samples that had been depletedunder both conditions with motifs not present in the Depletion reagent.An example of this analysis, shown in FIG. 24, indicates that removal ofcommon antibody specificities by the Depletion reagent can enhancedetection of remaining antibody specificities. Motif enrichmentincreased an average of 3-fold after DR depletion.

Although preferred embodiments of the present invention have been shownand described herein, it will be obvious to those skilled in the artthat such embodiments are provided by way of example only. Numerousvariations, changes, and substitutions will now occur to those skilledin the art without departing from the invention. It should be understoodthat various alternatives to the embodiments of the invention describedherein may be employed in practicing the invention. It is intended thatthe following claims define the scope of the invention and that methodsand structures within the scope of these claims and their equivalents becovered thereby.

REFERENCES

References referred to throughout this disclosure by bracketed numbers(e.g., [1], [2], etc.) are listed below. Each reference is incorporatedherein by reference in its entirety.

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The present application and invention further includes the subjectmatter of the following numbered clauses:

1. A method of identifying a plurality of peptides, comprising:providing a biological sample comprising a plurality of antibodies;contacting the biological sample with a plurality of peptides; andidentifying members of the plurality of peptides that form a complexwith members of the plurality of antibodies.

2. The method of clause 1, wherein the biological sample comprises abodily fluid.

3. The method of clause 2, wherein the bodily fluid comprises peripheralblood, lymphatic fluid, sweat, saliva, mucus, or a derivative of anythereof.

4. The method of any preceding clauses, wherein identifying members ofthe plurality of peptides that form a complex members of the pluralityof antibodies comprises sequencing a nucleic acid that encodes thepeptide.

5. The method of clause 4, wherein the sequencing comprises nextgeneration sequencing (NGS), Sanger sequencing, real-time PCR, orpyrosequencing.

6. The method of any of clausess 4-5, wherein each member of theplurality of peptides is coupled to a nucleic acid molecule encodingthat peptide.

7. The method of any of clauses 4-5, wherein the nucleic acid moleculecomprises deoxyribonucleic acid (DNA), ribonucleic acid (RNA), or aderivative of any thereof.

8. The method of clause 6, wherein each peptide is directly coupled toits corresponding nucleic acid molecule.

9. The method of clause 6, wherein each peptide is indirectly coupled toits corresponding nucleic acid molecule.

10. The method of clause 9, wherein the corresponding nucleic acidmolecule is within a vector that encodes the peptide.

11. The method of clause 10, wherein the vector is configured to expressthe peptide.

12. The method of clause 10, wherein the vector is comprised in a hostcell.

13. The method of clause 12, wherein the host cell expresses thepeptide.

14. The method of clause 13, wherein the peptide is expressed on thesurface of the host cell.

15. The method of any of clauses 12-14, wherein the host cell comprisesa microbial cell, a bacterial cell, an E. coli cell, a eukaryotic cell,a yeast cell, or a mammalian cell.

16. The method of any one of clauses 1-15, further comprising capturingmembers of the plurality of peptides that form a complex with members ofthe plurality of antibodies prior to identifying members of theplurality of peptides that form a complex with members of the pluralityof antibodies.

17. The method of clause 16, wherein the capturing comprises capturingthe peptide-bound members of the plurality of antibodies.

18. The method of clause 17, wherein the peptide-bound members of theplurality of antibodies are captured to a substrate.

19. The method of clause 18, wherein the substrate comprises a planarsurface or a plurality of microbeads.

20. The method of clause 19, wherein the plurality of microbeads aremagnetic or fluorescent.

21. The method of any one of clauses 17-20, wherein the bound members ofthe plurality of antibodies are captured using Protein A, Protein G,Protein L and/or an anti-immunoglobulin antibody or aptamer.

22. The method of any one of clauses 1-21, further comprising filteringthe plurality of antibodies prior to contacting the biological samplewith a plurality of peptides.

23. The method of clause 22, wherein the filtering comprises contactingthe plurality of antibodies with at least one reagent configured todeplete antibodies that bind to assay components other than theplurality of peptides.

24. The method of clause 23, wherein the at least one reagent comprisesthe host cell.

25. The method of any one of clauses 1-24, further comprising filteringthe plurality of peptides prior to contacting the biological sample witha plurality of peptides.

26. The method of clause 25, wherein the filtering the plurality ofpeptides comprises contacting the plurality of peptides with at leastone reagent configured to deplete peptides that form a complex withassay components other than the plurality of antibodies.

27. The method of clause 26, wherein the at least one reagent configuredto deplete peptides comprises Protein A, Protein G, Protein L, and/or ananti-immunoglobulin antibody or aptamer.

28. The method of any of clauses 1-27, further comprising determining atleast one peptide motif from the members of the plurality of peptidesidentified in c).

29. The method of clause 28, wherein determining the at least onepeptide motif comprises aligning the sequences of the members of theplurality of peptides identified in c).

30.The method of clause 29, wherein the aligning comprises using acomputational alignment algorithm.

31. A method of identifying at least one peptide indicative of aphenotype in a biological sample comprising: (a) identifying a pluralityof peptides in the biological sample according to any one of clauses1-30; (b) comparing the presence or level of each member of theplurality of peptides identified in a) to a reference value; and (c)identifying a peptide with a presence or level that differs from thereference based on the comparison in b), thereby identifying the atleast peptide indicative of the phenotype.

32. The method of clause 31, wherein the reference value for each memberof the plurality of peptides comprises a presence or level of thatmember of the plurality of peptides in a control sample.

33. A method of identifying at least one peptide motif indicative of aphenotype in a biological sample comprising: (a) identifying at leastone peptide motif in the biological sample according to any one ofclauses 28-30; (b) comparing the presence or level of the at least onepeptide motif identified in step a) to a reference value; and (c)identifying at least one peptide motif with a presence or level thatdiffers from the reference based on the comparison in b), therebyidentifying the at least one peptide motif indicative of the phenotype.

34. The method of clause 33, wherein the reference value comprises apresence or level of the same peptide motif in a control sample.

35. A method of characterizing a phenotype in a biological samplecomprising: (a) identifying a plurality of peptides in the biologicalsample according to any one of clauses 1-30; (b) comparing the presenceor level of each member of the plurality of peptides identified in a) toa reference value; and (c) identifying a peptide with a presence orlevel that differs from the reference based on the comparison in b),thereby characterizing the phenotype.

36. The method of clause 35, wherein the reference value for each memberof the plurality of peptides comprises a presence or level of thatmember of the plurality of peptides in a control sample.

37. A method of characterizing a phenotype in a biological samplecomprising: (a) identifying at least one peptide motif in the biologicalsample according to any one of clauses 28-30; (b) comparing the presenceor level of the at least one peptide motif identified in step a) to areference value; and (c) identifying at least one peptide motif with apresence or level that differs from the reference based on thecomparison in b), thereby identifying the at least one peptide motifindicative of the phenotype.

38. The method of clause 37, wherein the reference value comprises apresence or level of the same peptide motif in a control sample.

39. The method of any one of clause 32, 34, 36 or 38, wherein thecontrol sample has a different phenotype than the biological sample.

40. A method comprising detecting at least one peptide in a biologicalsample, wherein optionally the detecting is used to characterize aphenotype.

41. The method of clause 39 or clause 40, wherein the phenotypecomprises a disease or disorder.

42. The method of any one of clauses 35, 37 or 40, wherein thecharacterizing comprises a diagnosis, prognosis or theranosis of thedisease or disorder.

43. The method of any of clauses 35, 37 or 40, wherein thecharacterizing comprises determining a stage, grade, progression,treatment regimen and/or treatment response of the disease or disorder.

44. The method of any one of clauses 41-43, wherein the disease ordisorder comprises an infectious, autoimmune, parasitic, allergic,oncological, neurological, cardiovascular, pregnancy-related orendocrine disease or disorder.

45. The method of any one of clauses 41-43, wherein the disease ordisorder comprises an infectious disease or an autoimmune disease.

46. The method of any one of clauses 41-43, wherein the disease ordisorder comprises Celiac disease (CD), Sjogren's Syndrome (SS),Myasthenia Gravis (MG), preeclampsia (PE), systemic lupus erythematosis(SLE), Epstein-Barr virus (EBV), rhinovirus, cytomegalovirus (CMV),Streptococcus, human immunodeficiency virus (HIV), Haemophilusinfluenza, Chagas disease or Lyme disease.

47. The method of any one of clauses 41-43, wherein the disease ordisorder comprises a microbial infection, viral infection, bacterialinfection or fungal infection.

48. A peptide comprising a sequence in any of SEQ ID NOs.1-868.

49. A composition comprising at least one peptide of clause 48.

50. Use of at least one reagent to carry out the method of any ofclauses 1-47.

51. The use of clause 50, wherein the at least one reagent comprises atleast one of at least one peptide from any of SEQ ID NOs.1-868; apeptide library display system; an antibody binding agent; a primer set;and a depletion reagent.

52. The use clause 51, wherein the peptide library display systemcomprises an E. coli display system.

53. The use of clause 51, wherein the peptide library display systemcomprises a naïve peptide library.

54. The use of clause 51, wherein the peptide library display system isconfigured to characterize a phenotype

55. A kit comprising at least one reagent to carry out the method of anyof clauses 1-47.

56. The kit of clause 55, wherein the at least one reagent comprises atleast one of at least one peptide from any of SEQ ID NOs.1-868; apeptide library display system; an antibody binding agent; a primer set;and a depletion reagent.

57. The kit of clause 56, wherein the peptide library display systemcomprises an E. coli display system.

58. The kit of clause 69, wherein the peptide library display systemcomprises a naïve peptide library.

59. The kit of clause 69, wherein the peptide library display system isconfigured to characterize a phenotype.

60. A composition comprising at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 65, 70, 75,80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 10000, or atleast 100000 peptides matching a peptide sequence in SEQ ID NOs.1-868.

61. A composition comprising a library of nucleic acids having sequencesencoding at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 65, 70, 75, 80, 90, 100, 200,300, 400, 500, 600, 700, 800, 900, 1000, 10000, or at least 100000peptides matching a peptide sequence in SEQ ID NOs.1-868.

62. A composition comprising host cells comprising a library of nucleicacids having sequences encoding at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10,11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 65, 70,75, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 10000, orat least 100000 peptides matching a peptide sequence in SEQ IDNOs.1-868.

63. The composition of clause 62, wherein the host cells comprisemicrobial cells, bacterial cells, E. coli cells, eukaryotic cells, yeastcells, or mammalian cells.

64. The composition of clause 62, wherein the host cells express thepeptides on their surface.

65. A method of depleting a biological sample of an antibody repertoire,comprising: (a) contacting the biological sample with a composition ofclauses 60 or 61; (b) separating the host cells from the biologicalsample, thereby depleting the biological sample of the antibodyrepertoire.

A method comprising using the depleted biological sample of clause 65 asthe biological sample in step a) of clause 65.

The various methods and techniques described above provide a number ofways to carry out the application. Of course, it is to be understoodthat not necessarily all objectives or advantages described can beachieved in accordance with any particular embodiment described herein.Thus, for example, those skilled in the art will recognize that themethods can be performed in a manner that achieves or optimizes oneadvantage or group of advantages as taught herein without necessarilyachieving other objectives or advantages as taught or suggested herein.A variety of alternatives are mentioned herein. It is to be understoodthat some preferred embodiments specifically include one, another, orseveral features, while others specifically exclude one, another, orseveral features, while still others mitigate a particular feature byinclusion of one, another, or several advantageous features.

Furthermore, the skilled artisan will recognize the applicability ofvarious features from different embodiments. Similarly, the variouselements, features and steps discussed above, as well as other knownequivalents for each such element, feature or step, can be employed invarious combinations by one of ordinary skill in this art to performmethods in accordance with the principles described herein. Among thevarious elements, features, and steps some will be specifically includedand others specifically excluded in diverse embodiments.

Although the application has been disclosed in the context of certainembodiments and examples, it will be understood by those skilled in theart that the embodiments of the application extend beyond thespecifically disclosed embodiments to other alternative embodimentsand/or uses and modifications and equivalents thereof.

Preferred embodiments of this application are described herein,including the best mode known to the inventors for carrying out theapplication. Variations on those preferred embodiments will becomeapparent to those of ordinary skill in the art upon reading theforegoing description. It is contemplated that skilled artisans canemploy such variations as appropriate, and the application can bepracticed otherwise than specifically described herein. Accordingly,many embodiments of this application include all modifications andequivalents of the subject matter recited in the claims appended heretoas permitted by applicable law. Moreover, any combination of theabove-described elements in all possible variations thereof isencompassed by the application unless otherwise indicated herein orotherwise clearly contradicted by context.

All patents, patent applications, publications of patent applications,and other material, such as articles, books, specifications,publications, documents, things, and/or the like, referenced herein arehereby incorporated herein by this reference in their entirety for allpurposes, excepting any prosecution file history associated with same,any of same that is inconsistent with or in conflict with the presentdocument, or any of same that may have a limiting affect as to thebroadest scope of the claims now or later associated with the presentdocument. By way of example, should there be any inconsistency orconflict between the description, definition, and/or the use of a termassociated with any of the incorporated material and that associatedwith the present document, the description, definition, and/or the useof the term in the present document shall prevail.

In closing, it is to be understood that the embodiments of theapplication disclosed herein are illustrative of the principles of theembodiments of the application. Other modifications that can be employedcan be within the scope of the application. Thus, by way of example, butnot of limitation, alternative configurations of the embodiments of theapplication can be utilized in accordance with the teachings herein.Accordingly, embodiments of the present application are not limited tothat precisely as shown and described.

What is claimed is:
 1. An array comprising an array surface and at leastfive peptide probes, wherein each of the at least five peptide probescomprises a binding motif of 5 to 10 amino acids, wherein the bindingmotif is selected from the group consisting of W[YK]Wx[PA]K (SEQ ID NO:612), KxExH[NK]F (SEQ ID NO: 613), QxxxWPYxK (SEQ ID NO: 614), YxFDxNxR(SEQ ID NO: 615), FxWN[VI]P (SEQ ID NO: 616), [FW][LM]EXAH (SEQ ID NO:617), DF[LI]xAT (SEQ ID NO: 618), KxMSxFV (SEQ ID NO: 619), W[YK]Wx[PA]K(SEQ ID NO: 620), KxExH[NK]F (SEQ ID NO: 621), QxxxWPYxK (SEQ ID NO:622), WPT[SF]T (SEQ ID NO: 623), WP[TA]GR (SEQ ID NO: 624), KNWPx[GF](SEQ ID NO: 625), KxxP[LI]FA (SEQ ID NO: 626), WPxGQV (SEQ ID NO: 627),[VI][LR]KDF (SEQ ID NO: 628), WPT[SF]T (SEQ ID NO: 629), Kx[IM][VN]xWA(SEQ ID NO: 630), [YW]TxEPF (SEQ ID NO: 631), [AM][PTS]WExF (SEQ ID NO:632), R[PT][RTK]F[NS] (SEQ ID NO: 633), VY[SA]HW (SEQ ID NO: 634),[WF]xxKPxWxxM (SEQ ID NO: 635), KGx[SA]HxF (SEQ ID NO: 636), KGxVxF [AS](SEQ ID NO: 637), [IV]xHxTID (SEQ ID NO: 638), MLSXXVN (SEQ ID NO: 639),KxYSxxVR (SEQ ID NO: 640), Kx[VK]VNP (SEQ ID NO: 641), and wherein theat least five peptide probes extend from the array surface.
 2. The arrayof claim 1, wherein the at least five peptide probes are capable ofbinding to an antibody associated with Anaplasma phagocytophiluminfection.
 3. The array of claim 1, wherein the array surface comprisesa solid surface.
 4. The array of claim 3, wherein the solid surfacecomprises a microparticle.
 5. The array of claim 1, wherein the arraysurface comprises a biological particle.
 6. The array of claim 5,wherein the biological particle comprises a cell, a virus, or abacteriophage.
 7. The array of claim 6, wherein the biological particleis an Escherichia coli cell.
 8. The array of claim 5, wherein the arraysurface comprises a plurality of the biological particles, wherein eachof the plurality of the biological particles comprises a single speciesof the at least five peptide probes.
 9. The array of claim 1, whereinthe at least five peptide probes comprises at least a portion of anEscherichia coli eCPX scaffold.
 10. The array of claim 1, wherein the atleast five peptide probes further comprises a label.
 11. A method ofdiagnosing Anaplasma phagocytophilum infection in a subject comprising:contacting the array of claim 1 with a biological sample from thesubject, wherein the biological sample comprises a plurality ofantibodies; incubating the biological sample and the array underconditions sufficient for binding of each of the at least five peptideprobes to its target antibody; and measuring the binding of the at leastfive peptide probes to its target antibody in the biological sample. 12.The method of claim 11, wherein the method further comprises contactingthe biological sample with at least one reagent configured to removeantibodies that bind to array components other than the at least fivepeptide probes before contacting the array of claim 1 with a biologicalsample from the subject.
 13. The method of claim 12, wherein the atleast one reagent is the array surface free of the at least five peptideprobes.
 14. The method of claim 11, wherein the measuring comprises anELISA assay.
 15. The method of claim 11, wherein the measuring comprisesa peptide library display system.
 16. The method of claim 15, whereinthe peptide library display system comprises an E. Coli display system.17. The method of claim 11, wherein the measuring comprises detectingbinding of at least three of the at least five peptide probes to theirtarget antibodies.
 18. The method of claim 17, wherein the binding ofthe at least three peptide probes to their target antibodies indicatesthe subject is positive for Anaplasma phagocytophilum infection.
 19. Themethod of claim 11, wherein the measuring comprises detecting binding oftwo of the at least five peptide probes to their target antibodies. 20.The method of claim 19, wherein the binding of the two peptide probes totheir target antibodies indicates the subject is indeterminate forAnaplasma phagocytophilum infection.
 21. The method of claim 11, whereinthe measuring comprises detecting binding of one of the at least fivepeptide probes to its target antibody or no binding of the at least fivepeptide probes to its target antibody.
 22. The method of claim 21,wherein the binding of the one peptide probe to its target antibody orthe no binding of the at least five peptide probes to its targetantibody indicates the subject is negative for Anaplasma phagocytophiluminfection.
 23. The method of claim 11, wherein the measuring comprisescalculating the sum of z-scores for the at least five peptide probes.24. The method of claim 11, wherein the biological sample comprises abodily fluid.
 25. The method of claim 24, wherein the bodily fluid isperipheral blood, lymphatic fluid, sweat, saliva, or mucus.
 26. Themethod of claim 11, wherein the method has a sensitivity of at least99%.
 27. The method of claim 11, wherein the method has a specificity ofat least 99%.
 28. The method of claim 11, wherein the method has asensitivity of at least 99% and a specificity of at least 99%.
 29. A kitfor diagnosing Anaplasma phagocytophilum infection, comprising the arrayof claim 1 and a system for detecting the binding of each of the atleast five peptide probes to its target antibody.
 30. The kit of claim29, further comprises an agent for removing antibodies that bind toarray components other than the at least five peptide probes.